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 effective data retrieval, vari-ous extensions were done including the tolerance of errors in keyword matching and the search-as-you-type feature us-ing prefix matching. We present MESA, a map application to support different variants of spatial keyword query. In this demonstration, we adopt the autocompletion paradigm that generates the initial query as a prefix 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-fix/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 efficiency 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 different users. 1