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From Ken Krugler <kkrugler_li...@transpac.com>
Subject Re: How to compute the simlarity of a web page?
Date Wed, 25 Feb 2009 19:46:11 GMT
FWIW, we did something similar with our vertical 
crawl for Krugle. For each web page, we'd 
generate a TreeMap of terms/frequencies. Then 
we'd calculate the angle between this term vector 
representation, and a target term vector we 
generated by analyzing many "good" pages.

Since we were using Nutch, we'd use this score to 
adjust the OPIC weights for the outlinks, thus 
focusing the crawl on pages referenced by what we 
considered to be "good" pages. Though the way 
Nutch used OPIC made it highly susceptible to 
spammy link farms, so you'd need to add code to 
guard against that if you take this approach.

Note that most of the work here will be in 
analyzing the results and then tuning your target 
term vector - e.g. which terms (stop words) do 
you ignore, should you use unit vectors (all 
frequencies set to 1), what set of data do you 
use to generate the target term vector, etc.

Something we didn't do, which seemed valuable, 
would be to use phrases vs. single terms, along 
the lines of Amazon's SIPs (statistically 
improbable phrases).

-- Ken


>çð 2009-02-16àÍìI 22:08 -0500ÅCGrant Ingersollé ì¼ÅF
>>  Hmmm, you might be able to do the following:
>  >
>  > Create a document in a memory index containing the web page
>>  Create a query from the keywords
>  > Do a search with the query against the memory index and see the score.
>  >
>  > Alternatively, you could use the corpus statistics plus to create a 
>>  term vector from the document (as if it were a member of the 
>>  collection) and then do the cosine calculation of that document with 
>>  your query (which you also calculated the weights for based on your
>  > collections stats)
>  >
>  > Last, it sounds like you are essentially describing a categorization 
>>  task.  Have a look at some categorization software (for instance,
>  > Mahout can do Naive Bayes categorization or some alternatives).
>  >
>  > Of course, I might be missing something in understanding what you are 
>>  asking, so feel free to give a shout back to discuss.
>  >
>>  HTH,
>>  Grant
>>
>>  On Feb 12, 2009, at 1:31 AM, renavatior wrote:
>>
>>  >
>  > > I am doing some research in vertical search? Therefore, i defined some
>>  > weights of several keywords in my corpus expressing a certain
>>  > theme,later,how can i use these to compute the similarity with the 
>>  > given web
>>  > page(passed by url to the compute method).I saw the source code of
>>  > Similarity.java in Lucene,but i do not know how to use the method 
>>  > such as
>>  > TF,IDF,and so on.
>>  > i will really appreciate it if anyone can give me some advice,thanks
>  > > in
>>  > advance.
>>  > --
>>  > View this message in context: 
>>http://www.nabble.com/How-to-compute-the-simlarity-of-a-web-page--tp21970680p21970680.html
>>  > Sent from the Lucene - Java Users mailing list archive at Nabble.com.
>>  >
>>  >
>>  > ---------------------------------------------------------------------
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>>  >
>>
>>  --------------------------
>>  Grant Ingersoll
>>  http://www.lucidimagination.com/
>>
>>  Search the Lucene ecosystem (Lucene/Solr/Nutch/Mahout/Tika/Droids) 
>>  using Solr/Lucene:
>>  http://www.lucidimagination.com/search
>>
>>
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-- 
Ken Krugler
+1 530-210-6378

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