search - Combining TF-IDF (cosine similarity) with pagerank? -



search - Combining TF-IDF (cosine similarity) with pagerank? -

given query have cosine score document. have documents pagerank. there standard way of combining two?

i thinking of multiply them

total_score = cosine-score * pagerank

because if low on either pagerank or cosine-score, document not interesting.

or preferable have weighted sum?

total_score = weight1 * cosine-score + weight2 * pagerank

is better? might have 0 cosine score, high pagerank, , page show among results.

the weighted sum improve ranking rule.

it helps break problem retrieval/ filtering step , ranking step. problem outlined weighted sum approach no longer holds.

the process outlined in this paper sergey brin , lawrence page uses variant of vector/ cosine model retrieval , seems kind of weighted sum ranking weights determined user activity (see section 4.5.1). using approach document 0 cosine not pass retrieval/ filtering step , not considered ranking.

search search-engine tf-idf cosine-similarity

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