Our experiments in the Robust track this year focused on predicting query difficulty and using this prediction for improving information retrieval. We developed two prediction alg...
Elad Yom-Tov, Shai Fine, David Carmel, Adam Darlow...
In document retrieval using pseudo relevance feedback, after initial ranking, a fixed number of top-ranked documents are selected as feedback to build a new expansion query model. ...
We introduce a new theoretical derivation, evaluation methods, and extensive empirical analysis for an automatic query expansion framework in which model estimation is cast as a r...
Query expansion is a long-studied approach for improving retrieval effectiveness by enhancing the user's original query with additional related words. Current algorithms for ...