co-citation SEO language

Co-citation in SEO language

1) Co-citation If your Link fall in the right category (or right linking neighborhood) then you have a good co-citation and if not then it is said to be a bad co-citation.

Confused? Let me explain about co-citation in SEO language.

Let's think you have Search Engine Optimisation Company and you are looking for quality back links from the relevant websites. Lets say you got a link on a page where your link looks like this:

1) Search engine Optimisation Company 2) Shoes company 3) Gifts company 4) Gift vouchers 5) Woodland shoes 6) Experience gifts

The most popular search engines continually making innovation in their algorithms to prevent the spamming or using any BLACK HAT SEO Techniques.

The search engines crawlers might relate your website theme with other websites links available on the same page. The back links / link partners should be linked with the relevant and themed website. Linking anywhere with any website invite to a trouble and it might cause a penalties from the major search engines.

Good Co-citation If you have a search engine optimisation (SEO) web site, then your possible niche could be websites related to search engine optimisation. So, if you link to search engine optimisation related websites, and then your co-citation would be falling in the search engine optimisation (seo) category. This is good co-citation (means linking to good neighborhood, which is search engine optimisation (seo) in this case).

Bad Co-citation Bad co-citation occurs when your website falls in search engine optimisation (seo) category and you link to gift category or any other irrelevant category - which affect your search engine rankings. 2) Canonical URL Google calls Canonicalization as the process for picking the best URL when there are many alternatives. Have a glance at domain URLs mentioned below www.example.com example.com/ www.example.com/index.html example.com/home.asp Most of the people would think that these are the same URLs but all URLs are completely unique and different. A web server could return completely different content for all the URLs above Let me Explain Canonical URL in More Details A Common SEO mistake made by many webmasters is that they are not consistent in cross linking across the entire website.

If some of your links go to the URL http://example.com, and the rest go to http://www.example.com/, your link popularity gets divided among these two URLs - thus affecting the page rank as well as the rankings for that URL. So, it is better to pick the URL that you want and use it consistently across your entire website, as well as for your incoming links. One cannot, however, control how other sites would link to their website. It is better to use one type of URL not to confuse the search engines crawlers and making the most of search engine optimization. Suppose you want your default URL to be http://www.example.com/. You can make your web server so that if someone requests http://example.com/, it does a 301 (permanent) redirect to http://www.example.com/. That helps Google know which URL you prefer to be canonical. Adding a 301 redirect is recommended if your website changes often (e.g. dynamic content, a blog, etc.).SEO experts are proactive and keep themselves up to date with the SEO techniques and Search Engine Algorithms. Our SEO experts work on latest and ethical Search Engine Optimisation (SEO) techniques to produce quality and great results to its clients.

Seo Updates

Search Engines Trust Older Websites

Why Does Google Trust Old Websites So Much?

Seo Updates

The Evolution of Natural Linking

• When the web was younger is was less spammy. When the web was less commercial a larger percentage of sites were created out of passion, and those who spammed generally were not link spammers. Most new websites are spam.
  
  
• When search was less sophisticated people linked out of necessity. Now that Google AdSense has commercialized links and search is more relevant, more webmasters require payment (ie: cash, building their ego, sharing and spreading their bias, etc.) to link to your site.
  
  
• Older sites are owned by webmasters who had enough time to forge social relationships, and build a natural link profile composed of quality organic links.

Why Search Engines Trust Older Websites

• Search relies on older content, creating self reinforcing authorities based on the principals of the filthy linking rich.
  
  
• Many people who own websites value them as their babies, and want far more than their fair market value for them. Quality websites are nowhere near as liquid in nature as links or content are.
  
  
• Newer websites can outrank old sites, but they have to be more remarkable or add more value to outrank older sites. This adding of value (through things like better formatting, more in depth coverage, more bias, more interactive content) adds value to Google, making their search service more useful.
  
  
• As the standards for information quality increase, Google can arbitrarily decide that they don't like you or your business model. Thus the web is a game of constant evolution. Today's marketing leading content site may be a thin spam site by 2010 standards. Today's average content site might be thin spam by 2008.
  
  
• Given that new content creation is largely dominated by blogs and social media, new links are largely a proxy for the strength of your public relations campaign. Thus, currently Google's search results are dominated by old sites and sites that are controversial and/or buzzworthy.
  
  
• There is an information pollution side effect caused by the growing competition for links, but currently Google does not factor that into their view of the web. If you buy a link you are bad. If you lie for a link and get an organic citation you are good. I am not sure how/if they ever intend to address this side effect.
  
  
  
  
  
  
  

  This Information seems to have revolved around three main areas: domain age, backlinks and PageRank.

  Domain Age

  It appears that Google is presently giving a lot of weight to the age of a domain and, in this SEO's opinion, disproportionately so. While the age of a domain can definitely be used as a factor in determining how solid a company or site is, there are many newer sites that provide some great information and innovative ideas. Unfortunately a lot of these sites got spanked in the last update.

  On this tangent I have to say that Google's use of domain age as a whole is a good filter, allowing them to “sandbox” sites on day one to insure that they aren't just being launched to rank quickly for terms. Recalling back to the “wild west days” of SEO when ranking a site was a matter of cramming keywords into content and using questionable methods to generate links quickly I can honestly say that adding in this delay was an excellent step that insured that the benefits of pumping out domains became extremely limited. So I approve of domain age being used to value a site – to a point.

  After a period of time (let's call it a year shall we) the age should and generally has only had a very small influence on a site's ranking with the myriad of other factors overshadowing the site's whois data. This appears to have changed in the recent update with age holding a disproportionate weight. In a number of instances this has resulted in older, less qualified domains to rank higher than newer sites of higher quality.

  This change in the ranking algorithm will most certainly be adjusted as Google works to maximize the searchers experience. We'll get into the “when” question below.

  Backlinks

  The way that backlinks are being calculated and valued has seen some adjustments in the latest update as well. The way this has been done takes me back a couple years to the more easily gamed Google of old. This statement alone reinforces the fact that adjustments are necessary.

  The way backlinks are being valued appears to have lost some grasp on relevancy and placed more importance on sheer numbers. Sites with large, unfocused reciprocal link directories are outranking sites with fewer but more relevant link. Non-reciprocal links lost the “advantages” that they held over reciprocal links until recently.

  Essentially the environment is currently such that Google has made itself more easily gamed than it was a week ago. In the current environment, building a reasonable sized site with a large recip link directory (even unfocused) should be enough to get you ranking. For obvious reasons this cannot (and should not) stand indefinitely.

  PageRank

  On the positive side of the equation, PageRank appears to have lost some of its importance including the importance of PageRank as it pertains to the value of a backlinks. In my opinion this is a very positive step on Google's part and shows a solid understanding of the fact that PageRank means little in terms of a site's importance. That said, while PageRank is a less than perfect calculation subject to much abuse and manipulation from those pesky people in the SEO community it did serve a purpose and while it needed to be replaced it doesn't appear to have been replaced with anything of substantial value.

  A fairly common belief has been that PageRank would be or is being replaced by TrustRank and Google would not give us a green bar to gague a site's trust on (good call Google). With this in mind one of two things has happened; either Google has decided the TrustRank is irrelevant and so is PageRank and decided to scrap both (unlikely) or they have shifted the weight from PageRank to TrustRank to some degree and are just now sorting out the issues with their TrustRank calculations (more likely). Issues that may have existed with TrustRank may not have been clear due to it's weight in the overall algorithm and with this shift reducing the importance of PageRank the issues that face the TrustRank calculations may well be becoming more evident

  In truth, the question is neither here nor there (as important a question as it may be). We will cover why this is in the ...

  Conclusion

  So what does all of this mean? First, it means that this Thursday or Friday we can expect yet another update to correct some of the issues we've seen rise out of the most current round. This shouldn't surprise anyone too much, we've been seeing regular updates out of Google quite a bit over the past few months.

  But what does this mean regarding the aging of domains? While I truly feel that an aging delay or “sandbox” is a solid filter on Google's part – it needs to have a maximum duration. A site from 2000 is not, by default, more relevant than a site from 2004. After a year-or-so the trust of a domain should hold steady or at most, hold a very slight weight. This is an area we are very likely to see changes in the next update.

  As far as backlinks go, we'll see changes in the way they are calculated unless Google is looking to revert back to the issues they had in 2003. Lower PageRank, high relevancy links will once again surpass high quantity, less relevant links. Google is getting extremely good and determining relevancy and so I assume the current algorithm issues has more to do with the weight assigned to different factors than an inability to properly calculate a links relevancy.

  And in regards to PageRank, Google will likely shift back slightly to what worked and give more importance to PageRank, at least while they figure out what went awry here.

  In short, I would expect that with an update late this week or over the weekend we're going to see a shift back to last week's results (or something very close to it) after which they'll work on the issues they've experienced and launch a new (hopefully improved) algorithm shift the following weekend. And so, if you've enjoyed a sudden jump from page 6 to top 3, don't pop the cork on the champaign too quickly and if you've noticed some drops, don't panic. More adjustments to this algorithm are necessary and, if you've used solid SEO practices and been consistent and varied in your link building tactics – keep at it and your rankings will return.

Sitemaps Protocol Cross Host Support

Sitemaps Protocol Scaled For Cross-Host Support

One sitemap may now support multiple sites on different hosts thanks to a new addition to the Sitemaps protocol.

One sitemap to rule them all? After today, the question will be "why not?"

The Yahoo Search blog announced an update to sitemaps during the SMX West event. Along with Google and Microsoft, Yahoo disclosed a new feature for cross-host support for sitemaps.

"To ensure validity of this metadata, Sitemaps have previously been required to be on the same host and path as the URLs they contain," Yahoo Search noted. "This requirement forced the Sitemaps files to be hosted on the same servers as the actual site content."

With the change, the sitemap may be hosted on a different host, with the ability to support multiple sites on separate hosts. Webmasters will need to add a line to their robots.txt file to direct crawlers to the differently-hosted sitemap.

The official Sitemaps FAQ has been updated to reflect the support for separately hosted sitemaps.

Seo Updates

Yahoo Search cited a couple of concerns from webmasters that led to this latest update. Webmasters wanted to be able to keep user-facing content separate from feeds, as well as the ability to manage a number of websites from one sitemap.

"We hope this enhancement helps address those needs," the announcement said.

Google dance started PR updates

Google dance started PR updates

All the web masters and SEO knows it very well Google PR Updates held after 3-6 months and we know it very well that last Google PR updates in January 2008. But I have a question mark on it. Because for my Blog Search engine updates After Google PR updates in January 2008 it is 0.But when today I log into my system it shows PR 3 For it.

We know it very well that Google is serving various Types of updates for PR Like wise:

TBPR Export

GDPR Export

BL Export

Algo Update

TB Program Version Change

Days

Regarding PR updates more related information read Page Rank Export Table Definitions

And now come to the topic again it seem to be very difficult to identify that that which export table is using by Google this time. Now the question is that can anybody tell that which table has been used last time and now which table is using by Google for updates in PR.

However it might be possible that Google dance again started but it’s for ranking not for PR. Here my motive for discussion regarding Google dance is that after each PR updates Possibility of Google dance increases. So now we have to ready for the Google dance again if it will be the PR updates or might be Page Rank Export .

After researching on internet I come to know that if any webmaster wants that Google show sites links for his sites then He/She has to be something remember in mind that whenever visitor visit on site he has only less number of option to browse the site means only few number of categories available there because it increase the traffic on some specific categories and Google can pick the categories easily and trace that these are the most used by the Visitors/User.

I hope this information is useful for every webmaster/SEO/Link builders. Might be possible I am not very clear on some topics so please give me your views on blog. So that the discussion carry on until we (webmaster/SEO/Link builders ) got the right and reasonable answers.

It seems unlike Google to issue two page rank updates within 3 months but there has been chatter that the next update is in progress. If you check your Page Rank using Dig Page Rank then you can see the data centers are being updated.

Before you get carried up in the hustle and bustle of all the forum posts and blog posts - remember a few key points about Page Rank:

1. Page rank does not determine traffic

2. Page Rank does not determine SERPS

3. Page Rank updates all the time, it just takes time for the green bar to update on toolbars

4. Linking for PR is against Google’s rules and not the right mentality

Seo Updates

Page Rank is a numeric value that represents “how important a page is on the web”. Page Rank is Google’s way of deciding importance of the page. It matters because it is one of the factors that determines ranking of a page in the search results. Page Rank is a link analysis algorithm which assigns a numerical measuring to each element of a hyperlinked set of documents, for the purpose of “measuring” its relavant importance within the set. The page rank of any web site depends on some factors. The factors are following:

1. Inbound links of the Page.

2. Outbound links of the page

3. Relavent Links

4. Link Structure of the web Page

5. Age of the website

6. Relavancy of internal pages

7. Anchor text which is used for link Building

8. High PR Link Exchange

and many more….

The Google Toolbar’s displays a green bar which displays a visited page’s PageRank as a whole number between 0 and 10. If any website or web page have 0 pr that means it does not have 0 pr besides it may be 0 to 0.99 but if it shows only round figures of the whole numbers. The Toolbar PageRank is republished about once every three months. Google has not disclosed the precise method for determining a Toolbar PageRank value. So last update of Google toolbar PR Update have come in last week of september and first week of october. Now we are waiting for Next PR Update. I think next PR update will come in...Hey it,s Started Now........

Google Sitelink Update February 2008

Google Sitelinks Update Feb 2008

Just done a search on Google and this site has received the Google sitelinks that I have been longing for (yes I am a huge nerd). It looks to have been a big update, the biggest ever in fact and tons of new sites have got them:

Site architecture and age seems to play an important roll in getting sitelinks, very few sites that are less then 6-8 months old have got them.

Here are a few links to help you get a better understanding:

What are Google Sitelinks - Search Engine Land

Explaining Google Sitelinks - Problogger

Google Sitelinks and Brand Domination - SEOmoz

Congratulations to everybody who has got the sitelinks.

Update: The update is not currently showing up on Google US, so you will have to visit Google UK to see the changes.

How to get Google Sitelinks for your website

Many webmasters wonder how they can make Google display additional Sitelinks for their websites. What exactly are Sitelinks, how can you get them and are they worth the effort?

What are Google Sitelinks?

Google Sitelinks are a collection of links that appears below the result of a website. These additional links link to main pages of the website. They are randomly and automatically chosen by Google's algorithm.

Many webmasters wonder how they can make Google display additional Sitelinks for their websites. What exactly are Sitelinks, how can you get them and are they worth the effort?

What are Google Sitelinks?

Google Sitelinks are a collection of links that appears below the result of a website. These additional links link to main pages of the website. They are randomly and automatically chosen by Google's algorithm.

As an example, here are the sitelinks that you get for HP.com when you search for "HP":

Sitelinks only appear for general search terms. You'll get Sitelinks if you search for "HP" but you won't get Sitelinks if you search for a term like "HP printer supplies". Sitelinks show up most often for searches on brand names.

Which links does Google use for the Sitelinks?

Google seems to use the first level links on a website for the Sitelinks. That means that all links that are not present on the homepage of your site won't be used as Sitelinks.

The links should be descriptive text links or image links with a descriptive IMG ALT attribute. JavaScript or Flash links are not considered for Sitelinks. Google uses 2 to 8 links for the Sitelinks of a website. Unfortunately, it's unclear how Google assigns the number of links to each website.

The text that is used for the Sitelinks can be the text that are used for the link (anchor text) on the homepage or the title of the linked page. It seems that Google prefers links that appear at the top of a web page.

How can you get Sitelinks for your website?

Unfortunately, there is nothing certain about Google's Sitelinks. The following factors seem to influence whether Google displays Sitelinks or not:

1. Your website must have a stable #1 ranking for the searched keyword. Other websites don't seem to get Sitelinks.
   
   
2. Your website must be at least 2 years old. It seems that younger websites don't get Sitelinks.
   
   
3. The number of searches and the number of clicks that your website gets for a certain keyword seem to be considered. Keywords that aren't searched often enough don't get Sitelinks. It also seems that your website has to get many clicks for the searched keyword.
   
   
4. The number of links that point to your website with the searched keyword as the anchor text seem to influence the creation of Sitelinks. Sitelinks only seem to appear for the main keywords of a website, not for all keywords for which a website is listed.

If your website meets these criteria Google might assign Sitelinks to your website for your most important keywords.

Sitelinks can be a nice addition for searches for general keywords but they usually won't appear for searches that consist of two to four words. These words are the most important keywords for website promotion and search engine optimization.

Seo Updates


Seems to be New Type Result Page

Google tests an additional search box within the search results

Google now sometimes adds an additional search box in the search results that allows searches to search within a site. For example, you'll get the additional search box if you search Google.com for "amazon", "ny times" or "wikipedia"and "cric info":

Except Sitelink i found a new type of result also. Look below

with the results it's also providing the Search button bar also. Yet Google is providing search bar also as i think reason behind that is provide sufficient or can be say more relevant result to search term and easily navigation in the site. For example you are looking for cric info and want to be got the result of any match. You can provide your query so that visitor landing page should be more appropriate and accurate.

What can i say about it. Tell me something about it. waiting for your response........

Link Exchange Seo Tips

Link Exchange Seo updates Tips

To bring your site in top 10 ranking in major search engines your site should have link popularity. Most of the seo experts rank well their web sites in major search engines Due to Link Exchange. Here are some seo tips tricks and techniques for link exchange, now it is your time to do that…….

Link exchanging seo tips, seo tricks and precautions

You should always try to exchange link with relative website so that your web site can get more valuable and huge traffic. If you are getting valuable traffic your website page rank will boost the reason is that visitor will devote some times if your site content good and you offering his desired services and solutions.

When you exchange links with other site always remind that description should be good and brief. So that visitor should know what solutions and services you are offering, it may be seo tips, seo services, internet marketing services, product etc.

Always try to exchange links with quality link partners it means their web site should have a greater page rank and as well as good ranking. As the search engines rely on quality linking so it plays a very important role in search engine optimization.

Make your anchor text (link text) mare descriptive so that visitor could easy get an quick idea about your website.

Always try to monitor all your partners' website whether they are loyal or not. It has been seen that most of the webmaster normally remove links from their site to increase the number of one way link or inbound links. It will result in increase their ranking but results in decrease in your website ranking. You should always remind not to remove your partner's links from your site.

Be aware from fraud. There are many sites which free for all links program. Their aim is fraud and fraud, they takes your email and address that results in spam mails in your inbox.

It is also to be noticed that link partner’s web page should be linked with the home page of your site. Otherwise it is not worthy.

If you have offering lots of services and many products then make proper category for that so that various link partners should be listed in their respective and relative category.

Don't make all world of your link text capital.

Don't request for link exchange if your website is under construction as many webmaster don't accepts these kinds of link exchanging request.

Don't try to show off and make false statements about your web site popularity, your link popularity and other major factors.

Keep try to update you self with new seo tips tricks and techniques, seo updates and latest seo tips and guidelines. Updating is the only secret to be a seo expert.

relative absolute interlinking seo tips

Relative and absolute interlinking

Always use absolute interlinking of the website instead of relative interlinking. Absolute interlinking is better and push your site up in search engine ranking.

What is absolute interlinking: All the links with full website url address is known as absolute interlinking for example if you have an website http://www.example.com then http://www.example.com/contact.html will be an example of absolute linking.

What is relative interlinking: as per the above example if you use “contact.html” only then it will be called relative interlinking. Always use “www” prefix before your domain name, like www.example.com.

Example:


Absolute linking:

http://www.example.com/contact.html


Relative Linking:

contact.html

Importance of Absolute interlinking or linking: if you link your website with absolute linking then search engine will consider that page only if you use both like “www” and without www then search engine will got confused and your ranking may suddenly down in search engine.

Second thing if you link your website as without www to other site or web directory then, back link will not be counted in With WWW Domain. It means loss of page rank and ranking. Your web page rank will be divided in two parts, one with “www” and other is without www.

How to solve the problem in Google: If you have mistakenly liked your website as without www prefix with some website or directories than Google has offer a webmaster tool that is preferred domain. What you need to do, just make your Gmail account, login in Google webmaster tool account and add your website sitemap in that. Google will show you two option one with with www and second is without www. Chose with www domain name option and submit.

How to add sitemap: Google has provided inbuilt tool for sitemaps. Just go for XML site map and put your website url, it will take few second to make your website xml sitemap. Just copy and paste it in your root directory and add it on Google webmaster tool also.

How to optimize a site, basically there are two types of optimization techniques on is on page and other is off page optimization. On page search engine optimization techniques is simple and very easy as you have total control over that but if we talk about off page seo then it seems to be some tricky and hard as compare to on page.

Lets we talk about on page seo tips and tricks, on page optimization includes keyword research, keyword frequency and keyword density, website title and its description, your site should be as per w3c, use off effective and well formed meta tags, use of absolute and relative interlinking, page size, images size, alt tag, use of flash etc are some important factors in on page optimization.

Absolute link and Relative Link

An absolute link defines a specific location of the Web file or document including: the protocol to use to get the document, the server to get it from, the directory it is located in, and the name of the document itself. Below is an example of an absolute link:

<#a href="http://www.domain.com/pagename.html">


With a relative link, the search engine spiders and browsers already know where the current document is located. Thus, if you link to another document in the same directory, you will not need to write out the full URL. Only the file name is necessary. Below is an example of a relative link:

<#a href="pagename.html">

Seo Updates

Yahoo Segmenting Webinto TopicalHierarchies

Yahoo on Segmenting Web Sites into Topical Hierarchies

On one level, a search engine indexes a web site by crawling that site one URL at a time, collecting information about what it finds at that address, and indexing the information found so that it can be served to visitors later.

But, the process can be more complicated than that.

For instance, a search engine may try to understand more about specific sites by collecting information on a site wide basis.

Site Wide Information about Web sites

Information that a search engine might look at about a web site on a site wide level might include:

• Detecting multiple possibly-duplicated pages from the same site;
• Determining entry points of a website;
• Identifying spam and porn sites;
• Detecting site-level mirrors,
• Extracting site-wide templates, and
• Visualizing content at the site level.

A search engine might also attempt to classify web sites based upon features found on the site, such as:

• Topics of each page,
• Internal hyperlinks on sites,
• Commonly linked-to entry points in sites, with their anchor-text,
• General external link structures,
• Directory structures of sites,
• Link and content templates present on sites,
• Description, title, and tags on key pages on sites, and so forth.

However, most of these approaches try to come up with an overall topic for a site, or for broad sections of a site, rather than for individual pages, and how those pages might be related to each other within a hierarchy.

Topic labels for web pages

A new patent application from Yahoo tells us about these site wide reasons and approaches to looking at a site to prepare us for a finer grained look at a site, in a way that explores how a search engine might attempt to understand different topics on the individual pages and segments of a site.

It might do this by looking at topic labels for specific pages (from places like links to individual pages from the Yahoo Directory, Wikipedia, the Open Directory, or other directories), and seeing how those labels might relate to each other within a topical hierarchy.

We are fortunate that the inventors of the patent filing also wrote a paper that covers a lot of the same ground, which explains the processes involved without a lot of the legal language found in the patent filing - Hierarchical Topic Segmentation of Websites.

System and method for hierarchical segmentation of websites by topic
Invented by Kunal Punera, Shanmugasundaram Ravikumar, and Andrew Tomkins
Assigned to Yahoo
US Patent Application 20080046429
Published February 21, 2008
Filed August 16, 2006

Abstract

An improved system and method is provided for hierarchical segmentation of websites by topic.

To do so, an organization of topics may be determined within directories of a website, the hierarchical arrangement of the web pages in the website may be segmented by topic, and the segments representing regions of coherent topics in the website directory may be output.

In an embodiment, a website directory may be converted into a binary tree and dynamic programming may be applied to iteratively determine whether to add a node of the tree to a segment representing a topic.

A node selection cost may be evaluated to determine whether to add a node of the tree as a segment representing a topic.

And a cohesiveness cost may be evaluated to determine how well a web page of the tree may be represented by its closest ancestral node that may be a segmentation point of a segment representing a topic.

Conclusion

The paper goes into a lot of the reasons why a search engine might want to segment the parts of a web site, and how it can use things like URL structures to help it do so.

What I found most interesting about the document was the change in focus of a search engine from crawling and understanding individual pages to understanding how pages within a site relate to each other.

How do the topics and parts of your web site relate to each other, and how might a search engine understand those relationships from different features and aspects of the site, and from links pointed to the pages of the site from other places?

Seo Updates

Google Process Detecting Duplicate Content

New Google Process for Detecting Near Duplicate Content { On Your Page }

A new patent application on near duplicate content from Google explores using a combination of document similarity techniques to keep searchers from finding redundant content in search results.

The Web makes it easy for words to be copied and spread from one page to another, and the same content may be found at more than one web site, regardless of whether its author intended it to be or not.

How do search engines cope with finding the same words, the same content, at different places?

How might they recognize that the pages that they would want to show searchers in response to a search query contain the same information and only show one version so that the searchers don’t get buried with redundant information?

Duplicate and Near-Duplicate Documents on the Web

Sometimes a creator of content might show that content on more than one page on purpose, such as when:

1. They provide a “mirror” of a site - A site, or pages on a site may be copied at different domains to stop potential delays that happen when lots of people attempt to request the same document at the same time, or to keep the delivery of pages from being slow.
2. There are different formatted versions of the document - plain text or HTML or PDF or a separate printable version of the same document may be available for viewers to choose from, and special versions for phones and PDAs may also be available.
3. Sometimes content is shared with other sources, such as news wire articles, or blog posts that are published at both a group blog and an individual’s blog.

Sometimes content may be duplicated at other pages regardless of its creator’s intent, such as when:

1. Someone took some or all of the content for republication pursuant to fair use, or in violation of copyright.
2. The publishing system used shows the content at more than one address on the same site, so that it may appear to be unique based upon being located at a different address.
3. Content was aggregated or incorporated into another source on the Web, such as in a mashup or search results, or in some other form.

There are other instances where content is duplicated on more than one page, or where documents are very similar. It makes sense for a search engine to try not to show the same content over and over again to a searcher in a list of search results.

It’s a challenge that search engineers need to meet carefully, because there are instances where duplicated content is legitimately on the Web, and other times when it is duplicated without permission and regardless of its creator’s copyright.

Recent Google Efforts towards Duplicate and Near Duplicate Content

One of the more interesting papers from Google employees last year gave a very good overview of processes to detect duplicate and near duplicate processes on web pages - Detecting Near Duplicates for Web Crawling (pdf).

In that paper, one of the processes described in detail was developed by Moses Charikar, a Princeton professor, who has worked for Google in the past. Moses Charikar also is listed as the inventor of a Google patent granted early last year, which discusses ways to detect similar content on the Web - Methods and apparatus for estimating similarity

This past week another Google patent application, from Monika H. Henzinger, explores how duplicate and near duplicate content might be detected at different web addresses. The patent application includes references to a number of different previous methods, including Dr. Charikar’s.

Detecting duplicate and near-duplicate files
Invented by Monika H. Henzinger
US Patent Application 20080044016
Published February 21, 2008
Filed August 4, 2006

The patent application explores how some different existing methods for detecting near duplicate content could be used together to try to identify near duplicates on the Web.

It provides citations to a number of documents on the Web that explore the topic of duplicate, and near duplicate content, including the following:

* Finding similar files in a large file system
* Scalable Document Fingerprinting
* Copy Detection Mechanisms for Digital Documents
* Syntactic Clustering of the Web
* Similarity Estimation Techniques from Rounding Algorithms (pdf)
* Similarity search system with compact data structures
* Methods for identifying versioned and plagiarised documents

From those documents, Dr. Henzinger tests and explores the documents from Andrei Z. Broder (Syntactic Clustering of the Web) and Moses Charikar (Similarity Estimation Techniques from Rounding Algorithms), and compares the approaches from each.

While there were differences in how effective these approaches were according to tests run, the conclusion about their effectiveness in the patent application was that “neither of the algorithms worked well for finding near-duplicate pairs on the same Website, though both achieved high precision for near-duplicate pairs on different Websites.”

We’re also told that:

In view of the foregoing, it would be useful to provide improved techniques for finding near-duplicate documents. It would be useful if such techniques improved the precision of the Broder and Charikar algorithms. Finally, it would be useful if such techniques worked well for finding near-duplicate pairs on the same Website, as well as on different Websites.

Using Multiple Similarity Techniques Together

Techniques similar to those described in the documents from Broder and Charikar could possibly be combined to work in sequence, to improve the dectection of similar documents. The patent filing provides a nice overview of how that combined process would work, and why it would be an improvement.

Boilerplate, Similarity Techniques, and Fingerprints

One reason why some of the near-duplicate document detection algorithms perform poorly on pairs of pages from the same site, according to Dr. Henzinger, is because of boilerplate text that appears on those pages. A boilerplate detection process might be used to remove or ignore that boilerplate content in near-duplicate document analysis. I wrote about other reasons why Google might look for boilerplate on pages recently in Google Omits Needless Words (On Your Pages?)

This patent application explored the possibility of using the Broder and Charikar processes together, but it could use other, or additional document similarity techniques.

One approach used to “fingerprint” the content on pages is in creating “tokens” from the content as described in Rabin’s Fingerprinting By Random Polynomials. We’re told that different fingerprinting approaches might also be used, such as those described in the Hoad and Zobel paper Methods for identifying versioned and plagiarised documents.

Conclusion

I wrote about some of the problems around duplicate content on web pages in Duplicate Content Issues and Search Engines, and the post includes links to a number of white papers and patent filings about duplicate content.

The process described in this new patent application doesn’t so much introduce a brand new method of identifying near duplicate content on pages as it comes up with an approach that takes advantage of other detection methods in a new way.

I didn’t go into a lot of specific details on how the different similarity processes work because those are detailed fairly deeply in the papers that I linked to, and the process described in this patent application doesn’t necessarily rely completely upon any one of those processes, but rather on the idea that multiple processes could be used together intelligently.

Seo Updates

Google Omits Needless Words

Google Omits Needless Words

A lot of web pages and documents reuse the same text in sidebars and in footers at the bottoms of pages, like copyright notices and navigation sidebars.

Computer programmers will sometimes use the term “boilerplate” code to refer to standard stock code that they often insert into programs. Lawyers use legal boilerplate in contracts - often the small print on the back of a contract that doesn’t change regardless of what a contract is about.

It might be a good step for a search engine to ignore boilerplate text when it indexes pages, or uses the content of pages to create query suggestions for someone using a desktop personalized search. Ignoring boilerplate in the same documents could be helpful when using those documents to rerank search results in personalized search.

New York Times Boilerplate

Is Google ignoring boilerplate on pages when it indexes those pages and tries to understand what the pages are about? Does it disregard the words in your copyright notice, or the use of “home” in your link to your homepage?

Do the words appearing as anchor text in links to other blogs in your blogroll get ignored when the search engine tries to understand what one of your blog posts is about?

Wikipedia Boilerplate

It’s difficult to tell how much attention Google might pay to your copyright notice, or an introductory blurb or disclaimer that might appear on all of your pages. If Google is paying attention to those words now, it might not pay as much attention to them in the future.

Google’s Next Generation Search Engine?

Google’s next generation search engine may look a little like a hybrid between their present Web search as well as their desktop and intranet search, with a number of additional features. I wrote about two patent applications that seem to be part of that search in Google on Desktop Search and Personal Information Management.

I also noted in that post that there are at least 50 patent applications in total that may be part of that future search engine, which are listed as “related applications” in a patent application published at WIPO titled Methods and Systems for Information Capture and Retrieval.

Many of those patent applications were originally filed with the US Patent and Trademark office in 2003 and 2004, and the direction that Google may follow in the future could include them, or it could go in another direction completely. But many of the ideas behind them may make their way into whatever path Google may follow.

Google and Boilerplate

I’m keeping an eye open for the publication of those 50 patent applications. One of them came out this week, focusing on ignoring boilerplate, which could be something useful for today’s Google. The patent filing is:

Systems and methods for analyzing boilerplate
Invented by Stephen R. Lawrence
US Patent Application 20080040316
Published February 14, 2008
Filed March 31, 2004

Abstract

Systems and methods for analyzing boilerplate are described. In one described system, an indexer identifies a common element in a plurality of related articles. The indexer then classifies the common element as boilerplate. For example, the indexer may identify a copyright notice appearing in a plurality of related articles. The copyright notice in these articles is considered boilerplate.

Text in documents (web pages, word documents, PDFs, and so on) on your hard drive, or browser cache, or in your web surfing history or favorites might be used to create queries based upon what you’ve been doing recently with those documents. Those queries might be shown in a sidebox on your computer screen, as an information resource that you can use if you want to find out more on the topic that you are writing about, or reading, or browsing.

Or that document information might be used to rerank search results, when you perform a search, to find stuff related to what you were doing on your computer recently, if it might be helpful.

Boilerplate language could be identified by the search engine in a few different ways when it looks at the text or other elements on a page. An example from the patent application is that “any text following the word ‘copyright’ is boilerplate.”

Other types of boilerplate might include navigational text, disclaimers, and text that appears on every page of a web site.

Important Terms and Concepts on Boilerplate

There are two different types of queries that may be used by this search system, looking at recently used and viewed pages to grab keywords for searches:

Implicit queries - the indexing program looks for boilerplate elements on pages, and content elements, and creates an implicit search query comprising a search term from a term found in the content area.

Explicit queries - the query system might remove or weigh down boilerplate when someone performs a search.

With both implicit and explicit queries, the relative importance of actual content is given higher weight than the boilerplate language. An article might not be indexed after the boilerplate has been removed, which would mean that only the non-boilerplate language is used to influence those queries.

Boilerplate - examples include headers, footers, and navigational elements that may occur on multiple articles. Boilerplate could be identified by analyzing a number of related articles, such as multiple web pages within a web site. Boilerplate might also be identified by analyzing a single article.

Identifying boilerplate - the indexer may identify a boilerplate element in a few different ways. One might be to analyze the frequency of terms and phrases in a number of related articles to identify common element. The indexer could then classify the common elements as boilerplate. For example, a phrase like “Copyright 2004,” appearing in a number of related articles could be see as boilerplate.

Spatial location of terms or phrases - common terms or phrases often occur at a particular positions in articles, and might boilerplate. For example, a common term often found at the bottom of an article might be a copyright notices.

Navigational elements as boilerplate - common phrases occurring at the same place at the top, left, and right of an article could be navigational elements. On a web site, navigational elements are links letting visitors go to certain sections of the site; such as links to the home page, or a help page, and other pages on a site.

Article markup indicating boilerplate - HTML markup code for common terms on pages might indicate that those terms are boilerplate. One example is java script used in navigational links to change the appearance of those links when someone moves a mouse pointer over the links. A score might be determined for common terms that have markup near them. Different weights might be assigned based upon different kinds of markup - so words in javascript links might be given a higher boilerplate weight then words in bold or italic HTML elements.

Some markup could reliably identify boilerplate when you are even just looking at one article, instead of seeing if the boilerplate appears on more than one page of the same site. For example, links are markup code, and links going to the home page of a site or a page ending in “help.html” or “copyright.html” could be considered boilerplate.

Predetermined terms and phrases as boilerplate - boilerplate could be identified based on a predetermined list of terms and phrases. For example, common navigational or legal terms, such as “Home”, “Help”, “Terms of Service”, and “Copyright” may be used on a page, and the sections of the page where those appear might be considered boilerplate. The sections may be sentences or paragraphs. The text appearing in those areas might not be considered boilerplate on other pages when they appear without the predetermined terms.

Frequently indexed terms as boilerplate - terms that appear often in many different articles might be more likely to be considered boilerplate than terms that rarely appear. Examples of terms like that are “home” and “contact us.” These terms appear very frequenly as hyperlinks on many pages available on the Web.

Common terms and phrases are sometimes not boilerplate - even though some phrases may occur on multiple related pages, that frequency of use may not be an indication that the phrase is boilerplate. For example, a site about astronomy may include the term “astronomy” in many or all pages, and that term is relevant and important.

Some Conclusions on Boilerplate

1. Keep in mind that a search engine may ignore text on pages that it may think is boilerplate.

2. If you want a search engine to pay attention to text upon pages, pay attention to where that text appears on a page, and how frequently the same text appears on more than one page.

3. Global navigation and site wide links appearing on pages might be viewed as boilerplate when it comes to the content of the pages those links appear upon, but the anchor text within them may still tell the search engine something about the pages that they point towards.

4. Google may or may not be using something like this now, but if they aren’t, they could be in the future.

Seo Updates

Yahoo Phrase Based Indexing Nutshell

Yahoo Phrase Based Indexing in a Nutshell

Search engines are getting smarter about the phrases that they see and understand online, and Yahoo recently published a patent application that describes a number of the ways that they learn about and understand the use of phrases in documents on the Web.

Exploring how Yahoo might use phrases to rerank search results may show how they may try to understand data from published documents on the Web, and from log files that collect information about the queries that people use when they search for information about different concepts.

From Keyword Matching to Phrase-Based Indexing

A page’s placement in search results for certain queries can involve looking at ranking criteria and algorithms applied to documents involving keywords in search queries for things like:

• The number of occurrences of the query terms on a page,
• How close those terms might be together (proximity), and;
• The placement of the terms on a page (the location and types of elements those words may be within).

Those kinds of signals don’t take into account the context of the search terms, related to other words on the same page. They also don’t try to understand when queries are used as meaningful phrases.

Concepts and Contexts

The Yahoo patent application tries to determine the context of one or more terms as a concept or phrase as it is associated with other related phrases upon a page, to identify the most relevant pages in response to a given search query. I’ve written about a similar Google approach in the past in a post titled Phrase Based Information Retrieval and Spam Detection

The Yahoo process is different, but there are a number of similar ideas.

System and method for determining concepts in a content item using context
Invented by Jignashu Parikh and John Thrall
Assigned to Yahoo
US Patent Application 20080033982
Published February 7, 2008
Filed: December 15, 2006

Abstract

The present invention is directed towards systems and methods for indexing one or more items of content. The method of the present invention comprises extracting one or more items of text from a given item of content.

The one or more items of extracted text are tokenized into one or more concepts. One or more related concepts associated with the one or more concepts are identified.

A support score is generated for the one or more concepts, and the item of content is index with the one or more concepts and the one or more associated support scores.

Identifying Concepts Associated with Pages

The patent filing gives us a number of technical details on how concepts, or phrases, might be identified. One of them is trying to capture meaningful phrases, or concepts.

A search engine may strip out content from web pages using a text extractor program, which may also steal metadata and other information related to specific pages.

That text extractor may also look for content left behind by the readers of pages - user generated tags that identify and describe what a page might be about.

To break the words upon a page into phrases, the search engine may look at them as combinations of one, two, three, and more combinations of words, which it would try to match up against phrases appearing in a concept directory.

So, a sentence like, “The quick brown fox jumps over the lazy dog,” might be broken down into a number of phrases like:

• The quick brown
• Quick brown fox
• Brown fox jumps
• Fox jumps over
• Jumps over the
• Over the lazy
• The lazy dog

The text and the tags describe what those pages are about, and are sent to a program that takes that data and uses an aboutness extractor to break the text down and match it with keyword phrases maintained in a concept dictionary, to see if they are listed there as concepts.

The keyword phrases in the concept dictionary are ones that appear frequently in places like the Web or a database list of user queries.

The aboutness extractor breaks text taken from a page into tokens (like “the quick brown fox”) and identifies how frequently keyword phrases found within a “concept dictionary” appear in that page. Keyword phrases that are located in both the concept dictionary and upon on a specific page comprise “concepts.”

The concepts appearing on a page and their frequency of use upon that page is identified and maintained by that aboutness extractor.

If none of the phrases extracted from pages also appear in the concept directory, they may not be used as concepts for this concept based indexing.

In addition to concepts, this system looks at the context that those concepts are used within.

The aboutness extractor identifies the frequency with which related concepts appear on a given page. A context dictionary maintains information identifying related concepts - one or more keywords and/or phrases associated with a given concept.

Phrases that appear upon the same page together regularly may be more likely to be related to a specific topic, and using the context dictionary to identify them might help in relating those pages to that topic.

Contexts Identified as Query Refinements

The context dictionary contains information about keyword phrases that people have used to refine their search queries. The context dictionary might also be used to store information identifying search queries during a given time period or query session.

For example, a search engine may receive a number of queries during a given time period. Those may be monitored to identify related keyword phrases, and to store them in the context dictionary.

When someone searches and their results aren’t relevant, or they receive too many results, they might change the search terms they used to redefine or narrow the scope of their query.

The refined terms might be sent to a context dictionary, where they might be considered as indications of related concepts (keyword phrases) and possibly associated with a concept in the concept dictionary.

Example

A searcher may look for “Toyota” and receive a number of results. They may then search for “Honda,” followed by a query for “Mitsubishi.” Similarly, another user may search for “Mitsubishi” and receive results, and then look for the term “Toyota.”

The search engine may monitor searchers’ queries and determine and determine that the terms “Honda,” “Mitsubishi,” and “Toyota” frequently appear in queries submitted by users during a given time period or query session. The search terms and queries and related keyword phrases may be maintained in the context dictionary.

These related keyword phrases may show up as suggestions shown by the search engine to searchers as suggested query refinements.

Co-occurrence { Seo Updates }

If these related phrases appear upon the same page, they may also help to provide a “context” for that page, helping the search engine know what the page is about.

The context dictionary might maintain information identifying frequently co-occurring keyword phrases on the Web, and upon a page. The search engine may monitor web pages to identify keyword phrases frequently co-exist on the same pages.

Example

The search engine may look at advertisements and web pages on sites and determine that keyword phrases “interest rates” and “mortgage” frequently co-appear in advertisements and web pages.

Similarly, the search engine may decide that the keyword phrases “patent” and “intellectual property” frequently co-appear on pages. Those frequently co-appearing keyword phrases may be recorded by the context dictionary.

Co-Occurence and Human Editors

The index of co-appearing keyword phrases in the context dictionary may be supplemented with information from a human editor, who identifies keyword phrases related to a given concept.

For example, a human editor may submit an index entry pair comprising the phrase and keyword “notebook computer, laptop,” indicating that the phrase “notebook computer” is associated with the keyword “laptop.”

Related Concepts

The “aboutness extractor” retrieves keyword phrases from the context dictionary associated with concepts from sites. The keyword phrases retrieved from the context dictionary are “related concepts” with respect to the concepts on a site.

The aboutness extractor will then look at sites to determine if related concepts in the context dictionary are present or absent, and store that information.

Using Frequency and Relatedness to Determine a Support Score for Phrases

The aboutness extractor uses the frequency of concepts appearing on a page, as well as information about the presence or absence of related concepts associated with a given concept on a page, to calculate a support score for concepts on a page.

The aboutness extractor may also use information from another information data store to calculate a support score for a given concept. That other information data store may contain human editorial information about the concepts that could be used to appropriately increase or discount (not all human editorial information is reliable) the support score for a given concept.

It could also maintain tags or metadata generated by users describing a given content item. If user generated tags or metadata for a page are similar or match concepts identified for a page, the support score for that page for that concept may be increased.

Concept Index

The search engine then creates a concept index with entries identifying the one or more concepts associated with pages and their support scores for concepts.

Dominant Concepts

A search engine might then create an index for “dominant” concepts associated with the pages received by a search engine. A dominant concept or concepts may be the concepts associated with one or more items of content (pages) with the greatest associated support scores, or supports scores over a certain support score threshold.

The patent application tells us that there are a number of well known models that could be used to determine “dominant” concepts for pages.

Matching Concepts with Queries During Searches

The search engine would sort through the concept index to find concepts matching or similar to the terms in a query received from a searcher.

Pages associated with the concepts matching or similar to a searcher’s query terms may be selected and added to a search result set. Those added pages may be sorted in descending order according to the support scores for the concepts with which the pages are associated. The sorted result sets may then be sent back to the searcher.

Dictionary Manager

A dictionary manager could provide periodic updates to the concept dictionary, context dictionary and the “other information” data store at the search engine.

When a searcher refines their query by adding words or removing words or modifying them, the query refinement might be sent to the concept dictionary. If pages are updated with additional content, the updates may be sent to the context dictionary to ensure the context dictionary maintains the most relevant information on keyword phrases associated with concepts.

Further, if a user submits a query to a search engine, the dictionary manager may update the concept dictionary query logs to reflect the user’s query.

How Concepts Associated with Pages are Identified

You’ll find lots of different types of documents in a search index, from static pages to blog posts to advertisements, as well as audio and video and ecommerce platform product pages.

In this concept index approach, a document is first selected from pages linked to in the search index.

Concepts (keyword phrases) associated with a selected page are identified by seeing if they are also listed in a concept dictionary which contains concepts taken from query logs or a body of documents like the Web.

Concepts and related concepts on the page are identified, as are keyword phrases associated with those concepts. Related concepts are kept in a context dictionary, and are identified using a number of different information retrieval techniques.

Keyword phrases related to concepts might be created using information taken from user query sessions involving one or more terms over a certain period of time or during a given search session.

A context dictionary might also be created using information from human editors, who may identify keyword phrases associated with concepts on pages.

A support score is calculated for concepts identified on pages. These scores are numbers indicating the relevancy of a page with a specific concept, and with related concepts.

An index may be created where an index entry is made up of a page, concepts associated with the page, and respective support scores for the concepts. The index generated may be used to locate pages responsive to search requests, such as user search queries.

Calculating Support Scores for Concepts Associated with Pages

I need to go back over some of the processes described above a little, to explain how support scores are calculated.

A page is selected, and text from the page is extracted, and possibly also tags (user created metadata) associated with the page may be extracted.

The extracted text is broken into concepts (keyword phrases), identified using a concept dictionary. Concept keyword phrases in the concept dictionary are keyword phrases frequently appearing on the Web or in query logs.

A concept is selected from the one or more concepts associated with a page by looking at the frequencies with which the concept appears upon a page (How often does a concept/phrase “wireless laptop” show up on a page, for example).

Related concepts are identified using a context dictionary index. For example, concepts related to “wireless laptop” may be the keyword “computer,” as well as the keyword “notebook.”

The page is searched to see if it contains those related concepts associated with the concept selected.

The frequency of the concept in the page selected, as well as the presence or absence of related concepts are used to calculate a support score for the selected concept.

A support score is calculated using a combination of concept frequency, a term frequency/inverse document frequency (”TF/IDF”) measure using the one or more terms comprising a concept, and query log history.

The tf/idf measure looks at how frequently a phrase is mentioned on the page compared to how frequently it might be mentioned in a body of documents like Yahoo’s Web index, or query log history.

When all concepts associated with the page selected have been analyzed, a concept index entry is made, taking the page selected, concepts associated with page, and the support scores corresponding to the concepts on the page.

The concept index may identify dominant concepts associated with each page. Dominant concepts are ones that may have a support score exceeding a given amount or threshold.

Using Concepts to Find Relevant Search Results

Again, repeating some of the processes describe above, here’s a summary of how concepts can be used to provide a searcher with relevant pages using concepts associated with pages listed in the concept index.

The search engine receives a searcher’s query.

The query is parsed to identify the terms within the query.

A concept index is accessed, which contains pages, concepts associated with pages, and support scores for the concepts on those pages.

A page is selected from the pages listed in the concept index.

A check is performed to see if the concepts associated with the page matches or is similar to the query.

Example, a query may be performed for the term “desktop computers.” A concept from a page in the concept index might be the phrase “wireless desktop computer,” matching the query “desktop computers.”

If the concepts associated with the page in the concept index match or are similar to the terms comprising the query, the content item and concepts matching or similar to the query, as well as support scores associated with the matching or similar concepts, are added to a result set.

After pages in the concept index have been analyzed, the pages in the search result set are sorted in descending order according to the support scores corresponding to the concepts with which a given page is associated, and are returned to the searcher.

Using Concepts to find Related Pages

In addition to helping with search results, this system may be used to provide integration of related pages.

Someone searches, and a concept index is created, with entries identifying concepts associated with pages. Phrases within the search query may be used to identify pages with concepts (keyword phrases), which match or are similar to the terms in the user search query.

Results are returned to the searcher, using the concept index approach.

If the searcher chooses a page from the results, concepts related to that page are identified.

A search can then be performed to identify pages in the concept index associated with the concepts that are associated with the selected page. So, a searcher may select a link to a page associated with concepts A, B, and C.

After that selection by the searcher, a search may be performed to identify one or more pages (content items) in the concept index that are associated with concepts A, B, or C.

The page is sent to the searcher, along with links to pages identified as being associated with the concepts associate with the original page.

The searcher is presented with the page selected, as well as links to pages, or portions of the pages, which are related to the selected page.

Conclusion

Understanding concepts, in the form of phrases that appear on pages may help a search engine understand the pages that a searcher is looking for when they submit a query.

For example, someone searching for “ice cream” isn’t just looking for pages where the words “ice” and “cream” appear together.

So, a page that contains the actual phrase “ice cream” plus some related phrases such as “desserts,” or “ice cream parlor,” or “homemade waffle cones,” is more likely a match for a search for “ice cream” than a page describing someone slipping on ice, when going to a store for cream for their coffee, that doesn’t contain related phrases like that.

A page that includes phrases such as “double scoop,” “gelato,” “waffle cones,” “chocolate,” but not the phrase “ice cream” might also be seen as a “related” page for pages about “ice cream.”

What does this mean for people writing web pages? For one thing, it might be helpful to use words as phrases that the page is about together upon the page a few times, as opposed to mostly including those words on the page separately from each other. For another, it can be helpful to include related phrases, to help the search engines understand the context of those phrases.

Google Algorithm Vs Seo webmasters

Here’s the problem: Google can only be successful as long as they deliver relevant search results to a vast Internet audience. If they fail to deliver appropriate search results people will stop using them and their paid-for services will decline. On the other hand, you as a business executive want access to Google’s vast audience, and the only way you think you can effectively gain this access is to appear on that first search page as close to the top as possible; and you really don’t give a damn how you get there. Enter the Search Engine Optimization Gurus, who provide the promise of survival of the most index-able. Don’t get be in a hurry, you will find lots of Seo gurus after result declares of this seocontest2008.

So now we have Google who’s success is based on delivering relevant searches and SEO companies intend on manipulating this ability to place their clients on page one near the top. Google of course being a smart bunch of guys foils the SEO’s by constantly changing their methods and algorithms and trumps them by placing paid-for results in the most prominent places. And the game continues, bringing in huge profits to Google and wonderfully large fees to the Search Engine Optimization experts, leaving you paying the shot with little to show for it.

In the same manner we find difficult to get our site on 1st position in the Google, due to the Google’s ever changing alogo’s and their way of indexing the pages in the given time. Many of us Seo’s think that, if Google will keeps on changing their methods of giving the ranking to any site in future than, How to find best possible ways of optimizing any site and setting up the better strategies ever?.

But any ways, all Seo and SEO UPDATES still using their brains for getting their site top in the Google for the term seocontest2008 to win the precious noble prize and am in a que as well.