Hi guys! I'm trying to implement a "related search" feature using the mahout libraries. The queries are used to retrieve a set of items memorized in a DB.
I have come up with this implementation: -treat queries as "Users" and items in the DB as "Items" -for each query entered in the search engine I memorize the text of the query and the first 10 items retrieved. (the user-item column contains the query id, the item id and the relevance score of the item for the query) -to compute searches related to the current search I use mahout's Tanimoto similarity to find the most similar "users", i.e. the queries which have more result items in common with the current query. Is there a way to improve what I have done? I'd like to increase the importance of a query according to its "popularity" (i.e. how many time the query was entered) and/or keep trace of the most clicked items instead of the first 10 items, but I can't figure out how to do it. Any ideas?
