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Hey everyone,
I am interested in doing some document clustering, and right now I am considering using TF-IDF for this.
If I am not wrong, TFIDF is particularly used for evaluating the relevance of a document given a query. If I do not have a particular query, how can I apply tfidf to clustering?
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i have downloaded source code of Term Frequency/Inverse Document frequency (TF-IDF) implementation in C# from http://www.codeproject.com/KB/cs/tfidf.aspx. but couldn't find way run and test pls help for that did any one having any documentation about Term Frequency/Inverse Document frequency (TF-IDF)…
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I need to compare documents stored in a DB and come up with a similarity score between 0 and 1.
The method I need to use has to be very simple. Implementing a vanilla version of n-grams (where it possible to define how many grams to use), along with a simple implementation of tf-idf and Cosine similarity…
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Hi,
I'm looking for a package (any language, really) that I can use on a corpus of 50 documents to perform interdocument similarity testing in various metrics, like tfidf, okapi, language models, lsa, etc.
I want as a result a document similarity matrix, i.e. doc1 is x% similar to doc2, etc... …
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I've to create a dataset from some text files, writing them as vectors of features.
Something like this:
doc1: 1,0.45 6,0.001 94,0.1 ...
doc2: 3,0.5 98,0.2 ...
...
each position of the vector represent a word, and the score is given by something like TF-IDF.
Do you know some library/tool/whatever…
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