توضیحات
ABSTRACT
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, 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 geotextual 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.
INTRODUCTION
With the proliferation of geographical applications, such as Google Earth and Foursquare, geo-textual data are becoming ubiquitous these days. To retrieve such geo-textual data effectively, recent studies focused on the processing of spatial keyword queries which retrieve data objects that match certain keywords within a spatial region [4]. Further enhancements of spatial keyword search are conducted in two ways. One is to support autocompletion using prefix matching [2], which returns data objects that satisfy the prefix matching condition within the query region. We refer it as spatial prefix search. Another extension is to allow the approximate matching, which tolerates the fuzzy matching between query keywords and data objects [9]. However, the fuzzy search applied in [9] modeled the approximate matching at word level, which requires users to type at least one full word in a query. This approach violates the concept of autocompletion because real-time search engines should be error-tolerant for autocompletion.
Year: 2014
Publisher : VLDB Endowment
By : Yuxin Zheng , Zhifeng Bao , Lidan Shou and Anthony K. H. Tung
File Information: English Language/ 4 Page / size: 1,039 KB
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سال : 2014
ناشر : VLDB Endowment
کاری از : Yuxin Zheng , Zhifeng Bao , Lidan Shou and Anthony K. H. Tung
اطلاعات فایل : زبان انگلیسی / 4 صفحه / حجم : KB 1,039
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