A Unified Processing Paradigm for Interactive Location-based Web Search

Wang, S, Bao, Z and Huang, S 2018, 'A Unified Processing Paradigm for Interactive Location-based Web Search', in Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, WSDM 2018, Marina Del Rey, CA, USA, 5-9 February 2018, pp. 601-609.


Document type: Conference Paper
Collection: Conference Papers

Title A Unified Processing Paradigm for Interactive Location-based Web Search
Author(s) Wang, S
Bao, Z
Huang, S
Year 2018
Conference name the Eleventh ACM International Conference on Web Search and Data Mining (WSDM 2018)
Conference location Marina Del Rey, CA, USA
Conference dates 5-9 February 2018
Proceedings title Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, WSDM 2018
Publisher ACM
Place of publication United States
Start page 601
End page 609
Total pages 9
Abstract This paper studies the location-based web search and aims to build a unified processing paradigm for two purposes: (1) efficiently support each of the various types of location-based queries (kNN query, top-k spatial-textual query, etc.) on two major forms of geo-tagged data, i.e., spatial point data such as geo-tagged web documents, and spatial trajectory data such as a sequence of geo-tagged travel blogs by a user; (2) support interactive search to provide quick response for a query session, within which a user usually keeps refining her query by either issuing different query types or specifying different constraints (e.g., adding a keyword and/or location, changing the choice of k, etc.) until she finds the desired results. To achieve this goal, we first propose a general Top-k query called Monotone Aggregate Spatial Keyword query-MASK, which is able to cover most types of location-based web search. Next, we develop a unified indexing (called Textual-Grid-Point Inverted Index) and query processing paradigm (called ETAIL Algorithm) to answer a single MASK query efficiently. Furthermore, we extend ETAIL to provide interactive search for multiple queries within one query session, by exploiting the commonality of textual and/or spatial dimension among queries. Last, extensive experiments on four real datasets verify the robustness and efficiency of our approach.
Subjects Database Management
Copyright notice © 2018 ACM. ISBN 978-1-4503-5581-0/18/02
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