Improving AbraQ: An Automatic Query Expansion Algorithm

Our previous research has developed AbraQ, an innovative automatic query expansion algorithm that automatically adds a term to a search query to improve the search results. AbraQ differs from other relevance feedback approaches in that it works independently of the quality of the original search result, which means it works well for hard search tasks when there are not any relevant documents retrieved for the original query. Our experiments showed that it significantly improved precision for hard search tasks with multi-aspect queries, while other query expansion techniques often improve recall with no positive effects on precision. This paper further introduces an improved version called AbraQ2, which changes the way in which aspect vocabularies are constructed, and introduces a new algorithm for automatic relevance judgments. Our experiments show that these improvements help to find better queries that return more relevant documents to the user.