Batch processing of Top-k Spatial-textual Queries

Choudhury, F, Culpepper, J, Bao, Z and Sellis, T 2018, 'Batch processing of Top-k Spatial-textual Queries', ACM Transactions on Spatial Algorithms and Systems, vol. 3, no. 4, pp. 1-40.

Document type: Journal Article
Collection: Journal Articles

Title Batch processing of Top-k Spatial-textual Queries
Author(s) Choudhury, F
Culpepper, J
Bao, Z
Sellis, T
Year 2018
Journal name ACM Transactions on Spatial Algorithms and Systems
Volume number 3
Issue number 4
Start page 1
End page 40
Total pages 40
Publisher Association for Computing Machinery
Abstract Since the mid-2000s, everal indexing techniques have been proposed to efficiently answer top-k spatial-textual queries. However, all of these approaches focus on answering one query at a time. In contrast, how to design efficient algorithms that can exploit similarities between incoming queries to improve performance has received little attention. In this article, we study a series of efficient approaches to batch process multiple top-k spatial-textual queries concurrently. We carefully design a variety of indexing structures for the problem space by exploring the effect of prioritizing spatial and textual properties on system performance. Specifically, we present an efficient traversal method, SF-Sep, over an existing space-prioritized index structure. Then, we propose a new space-prioritized index structure, the MIR-Tree to support a filter-and-refine based technique, SF-Grp. To support the processing of text-intensive data, we propose an augmented, inverted indexing structure that can easily be added into existing text search engine architectures and a novel traversal method for batch processing of the queries. In all of these approaches, the goal is to improve the overall performance by sharing the I/O costs of similar queries. Finally, we demonstrate significant I/O savings in our algorithms over traditional approaches by extensive experiments on three real datasets and compare how properties of different datasets affect the performance. Many applications in streaming, micro-batching of continuous queries, and privacy-aware search can benefit from this line of work.
Subject Database Management
Keyword(s) Spatial-textual queries
DOI - identifier 10.1145/3196155
Copyright notice © 2018 ACM
ISSN 2374-0353
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Citation counts: TR Web of Science Citation Count  Cited 2 times in Thomson Reuters Web of Science Article | Citations
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