Search shortcuts: a new approach to the recommendation of queries

The recommendation of queries, known as query suggestion, is a common practice on major Web Search Engines. It aims to help users to find the information they are looking for, and is usually based on the knowledge learned from past interactions with the search engine. In this paper we pro-pose a new model for query suggestion, the Search Shortcut Problem, that consists in recommending “successful ” queries that allowed other users to satisfy, in the past, similar infor-mation needs. This new model has several advantages with respect to traditional query suggestion approaches. First, it allows a straightforward evaluation of algorithms from available query log data. Moreover, it simplifies the ap-plication of several recommendation techniques from other domains. Particularly, in this work we applied Collaborative Filtering to this problem, and evaluated the interesting re-sults achieved on large query logs from AOL and Microsoft. Different techniques for analyzing and extracting informa-tion from query logs, as well as new metrics and techniques for measuring the effectiveness of recommendations are pro-posed and evaluated. The results obtained clearly show the importance of several of our contributions, and open an in-teresting field for future research