Click-through prediction when searching local businesses

Abstract

Local search engines allow users to issue queries with a geographical connotation, named local searches, against a business database. Local search differs from traditional search in that, in order to capture adequately the user behaviour, the relevance estimation must integrate geographical signals, such as distance. In this work we investigate the problem of estimating the click-through in local searches using standard search methods along with a set of geographical features and business related. Our approach is validated using the logs of a local search engine. The evaluation shows how the non-linear combination of features of business, geo-local and textual allow a significant improvement over state-of-the-art alternatives based on text relevance, distance and business reputation.