MESA: A map service to support fuzzy type-ahead search over geo-textual data

Geo-textual data are ubiquitous these days. Recent study on spatial keyword search focused on the processing of queries which retrieve objects that match certain keywords within a spatial region. To ensure e ective data retrieval, vari- ous extensions were done including the tolerance of errors in keyword matching and the search-as-you-type feature us- ing pre x matching. We present MESA, a map application to support di erent variants of spatial keyword query. In this demonstration, we adopt the autocompletion paradigm that generates the initial query as a pre x matching query. If there are few matching results, other variants are per- formed as a form of relaxation that reuses the processing done in earlier phases. The types of relaxation allowed in- clude spatial region expansion and exact/approximate pre- x/substring matching. MESA adopts the client-server ar- chitecture. It provides fuzzy type-ahead search over geo- textual data. The core of MESA is to adopt a unifying search strategy, which incrementally applies the relaxation in an appropriate order to maximize the eciency of query processing. In addition, MESA equips a user-friendly inter- face to interact with users and visualize results. MESA also provides customized search to meet the needs of di erent users.