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Host level spam detection PDF  | Print |  E-mail
Wednesday, 08 April 2009 08:24

Stay away from bad neighbourhoods!

For starters, what is web spam and what’s its function? In the patents we’re looking at today, they describe spam as websites constructed with random or targeted content and links in order to, “to trick the analysis algorithms used by search engines” into ranking the pages higher than they should (bit of an oxy moron play there). The end game of course being to monetize said traffic with varying forms of advertising… yada yada… we know the deal - And the fly in the ointment?

“However, achieving this is complicated because it can be difficult to identify spam hosts without manually reviewing the content of each host and classifying it as a spam or non-spam host

So what’s a search engine to do? Welcome to the world of rare AIR (Adversarial Information Retrieval). Last time out CJ was walking us through some methods of Paid Link detection and in the past we’ve covered link spam, phrase based and temporal spam detection methods ( to name a few) – this time we’re going to look at Host Level Spam Detection.

Stay away from bad neighbourhoods

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New Algo Changes at Google PDF  | Print |  E-mail
Tuesday, 24 March 2009 15:08

Is Google going to hijack your content?

There’s been a fair amount of buzz going around today about the ‘2 New Improvements at Google’, one of which (as noted by the Author ‘Ori Allon’ and Search Engine Land), if not both, are related to the ‘Orion’ acquisition back in 2006. It seems an interesting implementation of the technology given the hub-bub at the time.

Essentially, the algorithm detects related concepts to a query and then it “returns a section of those pages, and lists other topics related to the key word so users can pick the most relevant.” – Which is interesting as ‘sections’ really does start ringing bells for page segmentation for me. Anyway, that’s for another day.

Part one, the search refinements, are more of a categorization and concept targeting system. Now, the refinements are fine really, something we can deal with… the second part, longer snippets, is slightly more concerning.

Ori Allon

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Geo-targeting for Kingons; film at 11 PDF  | Print |  E-mail
Monday, 09 March 2009 09:21

How Google deals with language and location

When you think of geo-targeting for SEO, what springs to mind? If you said country and language go body slam something, you’re the next lucky contestant on ‘Guess that Algo’. If you said type in co-ordinates and send the intercontinental up their arses… Well, methinks it’s time for some anger management.  Oooo..look, butterfly..

Anyway, an interesting patent was awarded to the Google and it’s worth having a quick look at. The patent in question is;

Ordering of search results based on language and/or country of the search results – filed October 21, 2008 and awarded February 26 2009 - Gupta; Vineet; (Bangalore, IN) ; Gomes; Ben; (Mountain View, CA) ; Lamping; John; (Los Altos, CA) ; McGrath; Mizuki; (Minato-ku, JP) ; Singhal; Amitabh; (Palo Alto, CA) ; Tong; Simon; (Mountain View, CA)

And it has some author relations with;

System and method for providing preferred country biasing of search results – filed June 27, 2003 and awarded November 11, 2008
System and method for providing preferred language ordering of search results – filed April 3, 2003 and awarded November 11, 2008

Essentially what we have here looks like the two separate components and the new parent connector. This essentially works by

  1. Getting the search results (via existing ranking mechanisms)
  2. Sorting/re-ranking of results based on language/country
  3. Re-ranking of results based on region/language
  4. Delivery of new re-ordered results set

Ok, so what are the considerations you ask? And what does any of it have to do with Klingons? We’re getting to that….

Google geo-targeting for Klingons

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What can SEOs learn from Google Suggest? PDF  | Print |  E-mail
Monday, 16 February 2009 08:50

A journey into Google’s patent on generating suggestions

Search engines are always looking to make our lives easier, or at least accessing the world’s information in a timely manner. But in the old days they had to wait for the user to take action before they could begin to deliver potential results for a query – not these days – starting to gather search results and even implementing search assist can happen with each keystroke.

You know the one, the suggestions they make as you’re typing in a given query? It looks something like this;

Google Search Assist

I know more than a few SEO peeps have talked about this as a potential problem for some long tail targets and others have pondered if it would make a good keyword research tool. They can also use the same systems for query analysis as far as which documents to return and rank. But what if there is a potential for personalization of this data? Because there just might be; and that would certainly limit its overall effectiveness from a SEO perspective - At least as a research tool.

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Hunting for paid links; a technical review PDF  | Print |  E-mail
Thursday, 05 February 2009 07:57

(Note; the following is a guest post from my good friend Miss CJ)

How search engineers look for nepotistic links

Paid links are a bit of problem for search engine engineers because they can be misleading.  Some links are bought in order to boost rank and others are purchased for legitimate reasons, such as actually offering something interesting to a website visitor.  Not all links should be discounted but different weights can be given to allow less important links to get a full "vote". 

It's not easy to differentiate between these, but there has been a fair bit of research around it we can look at.  If search engines could discount misleading nepotistic links, their performance would improve.  In the SEO community, this would be received with mixed emotions not doubt.  Google uses methods to detect keyword spamming for example, and uses other text based methods, but their algorithm is open to link spam.

But what are search engineers doing to combat nepotistic links in modern information retrieval?

Are paid links worth it?

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