Orthogonal query recommendation

Abstract

One important challenge of current search engines is to satisfy the users' needs when they provide a poorly formulated query. When the pages matching the user's original key- words are judged to be unsatisfactory, query recommendation techniques are used to propose alternative queries and alter the result set. These techniques search for queries that are semantically similar to the user's original query, often searching for keywords that are similar to the keywords given by the user. However, when the original query is sufficiently ill-posed, the user's informational need is best met using entirely different keywords, and a substantially different query may be necessary. We propose a novel approach that is not based on the keywords of the original query. We intentionally seek out orthogonal queries, which are related queries that have (almost) no common terms with the user's query. This allows an orthogonal query to satisfy the user's informational need when small perturbations of the original keyword set are insufficient. By using this technique to generate query recommendations, we outperform several known approaches, being the best for long tail queries.

Additional details