Monday, October 20, 2008

Re: question about midterm

Recall that in relevance feedback, we show K docs to the user, who marks r of them to be relevant (and thus K-r of them to be irrelevant). We then compute the new query as alpha* old query +  beta*  (sum of relevant doc vectors)/r + gamma * (sum of irrelevant doc vectors)/(K-r).

Since we are showing only *one* document to the user (K=1) , and the user says it is relevant (r=1), we have to assume that the number of irrelevant documents that we have shown until now is 0; which means that gamma factor becomes zero.
[You can't assume that 1023 are irrelevant documents--we haven't shown them to the user--so how do we know that she would have found them to be irrelevant?]

3.[3pt] Suppose the user is shown D in response to the query Q, and the user says
that D is relevant to his query. If we now use relevance feedback to modify Q, what
will the query vector become? Assume that alpha, beta and gamma are all 1.


On Wed, Oct 15, 2008 at 8:59 AM, Farooq Khera <> wrote:
You were going to provide some insight about the specimen midterm about the question of Relevance feedback in reference to Irrelevant documents?
I was confused about how you calculate the sum of the irrelevant documents.  It would seem there are 1023 irrelvant documents.
and so we know the size of irrelvant documents, such that part of the formula is Gama/#of irrelvant documents * (Sum of (irrelvant document vectors))

However its not well defined what the irrelevant document vectors are?
Unless somehow you can just take the whole corpus as a vector and then just subtract whatever the relevant document parts... which makes sense now i think lol...

-Farooq Khera

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