Hi Aleksander,
Thanx for clearing this up. I am confident that this is a way to explore for me
as I'm just starting to grasp the matter. Do you know why I'm not getting any
results with the query posted earlier then? It gives me the folowing only:
<lst name="moreLikeThis">
<result name="18477975" numFound="0" start="0"/>
</lst>
Instead of delivering details of the interestingTerms.
Thanks in advance
Patrick
-----Original Message-----
From: Aleksander M. Stensby [mailto:[EMAIL PROTECTED]
Sent: woensdag 26 november 2008 13:03
To: solr-user@lucene.apache.org
Subject: Re: Keyword extraction
I do not agree with you at all. The concept of MoreLikeThis is based on the
fundamental idea of TF-IDF weighting, and not term frequency alone.
Please take a look at:
http://lucene.apache.org/java/2_4_0/api/org/apache/lucene/search/similar/MoreLikeThis.html
As you can see, it is possible to use cut-off thresholds to significantly
reduce the number of unimportant terms, and generate highly suitable queries
based on the tf-idf frequency of the term, since as you point out, high
frequency terms alone tends to be useless for querying, but taking the document
frequency into account drastically increases the importance of the term!
In solr, use parameters to manipulate your desired results:
http://wiki.apache.org/solr/MoreLikeThis#head-6460069f297626f2a982f1e22ec5d1519c456b2c
For instance:
mlt.mintf - Minimum Term Frequency - the frequency below which terms will be
ignored in the source doc.
mlt.mindf - Minimum Document Frequency - the frequency at which words will be
ignored which do not occur in at least this many docs.
You can also set thresholds for term length etc.
Hope this gives you a better idea of things.
- Aleks
On Wed, 26 Nov 2008 12:38:38 +0100, Scurtu Vitalie <[EMAIL PROTECTED]>
wrote:
> Dear Partick, I had the same problem with MoreLikeThis function.
>
> After briefly reading and analyzing the source code of moreLikeThis
> function in solr, I conducted:
>
> MoreLikeThis uses term vectors to ranks all the terms from a document
> by its frequency. According to its ranking, it will start to generate
> queries, artificially, and search for documents.
>
> So, moreLikeThis will retrieve related documents by artificially
> generating queries based on most frequent terms.
>
> There's a big problem with "most frequent terms" from documents. Most
> frequent words are usually meaningless, or so called function words,
> or, people from Information Retrieval like to call them stopwords.
> However, ignoring technical problems of implementation of
> moreLikeThis function, this approach is very dangerous, since queries
> are generated artificially based on a given document.
> Writting queries for retrieving a document is a human task, and it
> assumes some knowledge (user knows what document he wants).
>
> I advice to use others approaches, depending on your expectation. For
> example, you can extract similar documents just by searching for
> documents with similar title (more like this doesn't work in this case).
>
> I hope it helps,
> Best Regards,
> Vitalie Scurtu
> --- On Wed, 11/26/08, Plaatje, Patrick <[EMAIL PROTECTED]>
> wrote:
> From: Plaatje, Patrick <[EMAIL PROTECTED]>
> Subject: RE: Keyword extraction
> To: solr-user@lucene.apache.org
> Date: Wednesday, November 26, 2008, 10:52 AM
>
> Hi All,
> as an addition to my previous post, no interestingTerms are returned
> when i execute the folowing url:
> http://localhost:8080/solr/select/?q=id=18477975&mlt.fl=text&mlt.inter
> es tingTerms=list&mlt=true&mlt.match.include=true
> I get a moreLikeThis list though, any thoughts?
> Best,
> Patrick
>
>
>
>
--
Aleksander M. Stensby
Senior software developer
Integrasco A/S
www.integrasco.no
