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 nd 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 propose 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 information 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 simplies the application of several recommendation techniques from other domains. Particularly, in this work we applied Collaborative Filtering to this problem, and evaluated the interesting results achieved on large query logs from AOL and Microsoft. Dierent techniques for analyzing and extracting information from query logs, as well as new metrics and techniques for measuring the eectiveness of recommendations are proposed and evaluated. The results obtained clearly show the importance of several of our contributions, and open an interesting eld for future research.