Query Phrase Expansion using Wikipedia in Patent Class Search

Abstract

Relevance Feedback methods generally suffer from topic drift caused by words ambiguity and synonymous uses of words. As a way to alleviate the inherent problem, we propose a novel query phrase expansion approach utilizing semantic annotations in Wikipedia pages, trying to enrich queries with context disambiguating phrases. Focusing on the patent domain, especially on patent search where patents are classified into a hierarchy of categories, we attempt to understand the roles of phrases and words in query expansion in determining the relevance of documents and examine their contributions to alleviating the query drift problem. Our approach is compared against Relevance Model, a state-of-the-art, to show its superiority in terms of MAP on all levels of the classification hierarchy.