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MESA: a map service to support fuzzy type ahead search over geo-textual data
conference contribution
posted on 2023-05-23, 09:03 authored by Zheng, Y, Bao, Z, Shou, L, Tung, AKHGeo-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, various extensions were done including the tolerance of errors in keyword matching and the search-as-you-type feature using 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 performed as a form of relaxation that reuses the processing done in earlier phases. The types of relaxation allowed include spatial region expansion and exact/approximate prefix/substring matching. MESA adopts the client-server architecture. 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 interface to interact with users and visualize results. MESA also provides customized search to meet the needs of different users.
History
Publication title
Proceedings of the 40th International Conference on Very Large Data BasesVolume
7Editors
HV Jagadish, A ZhouPagination
1545-1548ISSN
2150-8097Department/School
School of Information and Communication TechnologyPublisher
Association for Computing MachineryPlace of publication
United States of AmericaEvent title
40th International Conference on Very Large Data BasesEvent Venue
Hangzhou, ChinaDate of Event (Start Date)
2014-09-01Date of Event (End Date)
2014-09-05Rights statement
Copyright 2014 the AuthorsRepository Status
- Restricted