Batch processing of Top-k Spatial-textual Queries

Farhana M. Choudhury, J. Shane Culpepper, Timos Sellis
<span title="">2015</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="" style="color: black;">Second International ACM Workshop on Managing and Mining Enriched Geo-Spatial Data - GeoRich&#39;15</a> </i> &nbsp;
Top-k spatial-textual queries have received significant attention in the research community. Several techniques to efficiently process this class of queries are now widely used in a variety of applications. However, the problem of how best to process multiple queries efficiently is not well understood. Applications relying on processing continuous streams of queries, and offline pre-processing of other queries could benefit from solutions to this problem. In this work, we study practical
more &raquo; ... ns to efficiently process a set of top-k spatial-textual queries. We propose an efficient best-first algorithm for the batch processing of top-k spatial-textual queries that promotes shared processing and reduced I/O in each query batch. By grouping similar queries and processing them simultaneously, we are able to demonstrate significant performance gains using publicly available datasets.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1145/2786006.2786008</a> <a target="_blank" rel="external noopener" href="">dblp:conf/sigmod/ChoudhuryCS15</a> <a target="_blank" rel="external noopener" href="">fatcat:3ygnep7fbrbmfdx75gx7ujlgb4</a> </span>
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