How can I model topics in the results returned by a search engine with higher weightage to documents ranked higher in the result set?
The use case that I am looking at involves extracting the most significant topics returned in the search results.
Eg. If the user searches for a query q1 which returns documents D1...Dn with scores S1...Sn (in descending order) then I propose the notion that the theme of such a set of documents is represented better by documents scored higher in the result set.
Is it possible to incorporate this information in to topic modelling algorithms like LDA?