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I have a corpora of queries and answers where the queries are the title of different documents and the answers are a short description of them. E.g:

Title: African Civilian Deaths

Description: How many civilian non-combatants have been killed in the various civil wars in Africa?

I have tried to build a DSSM model to compute the cosine similarity between a given title and the queries so I could print out the one with bigger similarity expecting to be the right one. For instance, when writing "African Civilian Deaths" I was expecting to get the description between the top 10 answers, which didn't get to happen being in the 45th place.

As I didn't succeed doing this I was wondering how could I do it using tf-idf. I know how to compute the relevance of each word in my documents and so on but I don't really know how to make the comparison... Or how to say that this description corresponds to the title. Therefore, my question is how could I use tf-idf for comparing a query and an answer to see how close they are. I want the real question to be at least in the top 10 of most similar answers.

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2 Answers 2

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With tf-idf, each of your queries and answers is a vector (whose size is the number of words in your corpora) in the tf-idf word-document matrix.

Then, you can do exactly what you did previously and use cosine similarities to determine proximity between your titles and your descriptions.

Tf-idf is just a way to transform a document (seen as a bag of words) into a numerical vector. It creates a tf-idf word-document matrix. Each line of this matrix "represents" a word and each column a document.

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  • $\begingroup$ I was think of another approach as the one with cosine similarity didn't give me good results. Something like compare the tf-idf value of the words in the documents with those in the queries or so as I am not interested in using DSSM now. $\endgroup$
    – Marisa
    Commented Apr 13, 2018 at 12:39
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If it is not the case that you have to implement everything from the scratch, perhaps of a research reason, you can use one of many information retrieval platforms whereby you can run popular retrieval methods like tf-idf, BM25, SDM, and so on. These are some that I have used:

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  • $\begingroup$ I have to implement it from zero... $\endgroup$
    – Marisa
    Commented Apr 13, 2018 at 12:41

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