PSQE: Personalized Semantic Query Expansion for user-centric query disambiguation

Abstract In Information Retrieval, query expansion refers to the procedure ofreformulating a user's search query by adding further search terms to theoriginal query to improve retrieval quality. Short queries, specifically, oftensuffer from ambiguity, i.e., they refer to multiple possible senses. Theobjective of query expansion, then, is to augment with terms that best match theuser's information need. In this work, we propose and analyse a system forsemantic query expansion that leverages contextual information extracted fromuser profiles to generate queries capable of disambiguating multi-sense searchqueries. We generate synthetic profiles from a knowledge graph of Wikipediaarticles, on which we train individual word2vec embeddings. Using a k-nearestneighbour search, we determine semantically close keywords to append to a givenquery. We evaluate this user-centric approach across corpora of varying sizes,assessing the extent to which sentinel articles are retrieved. Our findingssuggest that tailoring the expansion to the user's context results in animprovement of median rank by 2 levels, and an increase in category retrievalamong the top three results of 6% on average.