Discovering co-located queries in geographic search logs

A geographic search request contains a query consisting of one or more keywords, and a search-location that the user searches for. In this paper, we study the problem of discovering co-located queries, which are geographic search requests for nearby search-locations. One example co-located query pattern is {"shopping mall", "parking"}. This pattern indicates that people often search "shopping mall" and "parking" over locations close to one another. Co-located queries have many applications, such as query suggestion, location recommendation, and local advertisement. We formally define co-located query patterns and propose two approaches to mining the patterns. Our basic approach is based on an existing spatial mining algorithm. To find more specific co-located queries that only appear in specific regions, we propose a lattice based approach. It divides the geographic space into regions and mines patterns in each region. We also define a locality measure to categorize patterns into local and global. Experimental results show that the lattice based approach outperforms the basic approach in the number of patterns, the quality of patterns, and the proportion of local patterns.