Automatic query recommendation using click-through data

Abstract

We present a method to help a user rede ne a query suggesting a list of similar queries. The method proposed is based on clickthrough data were sets of similar queries could be identi ed. Scienti c literature shows that similar queries are useful for the identi cation of di erent information needs behind a query. Unlike most previous work, in this paper we are focused on the discovery of better queries rather than related queries. We will show with experiments over real data that the identi cation of better queries is useful for query disambiguation and query specialization.