SKPS: Towards efficient processing of spatial-keyword publish/subscribe system

Wang, X; Yang, S; Zhang, Y

SKPS: Towards efficient processing of spatial-keyword publish/subscribe system

Wang, X Yang, S Zhang, Y

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, 9877 LNCS pp. 444 - 447
Issue Date:: 2016-01-01

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Field	Value	Language
dc.contributor.author	Wang, X	en_US
dc.contributor.author	Yang, S	en_US
dc.contributor.author	Zhang, Y https://orcid.org/0000-0002-2674-1638	en_US
dc.date.issued	2016-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, 9877 LNCS pp. 444 - 447	en_US
dc.identifier.isbn	9783319469218	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/101307
dc.description.abstract	© Springer International Publishing AG 2016. With the popularity of geo-equipped devices and location based services, spatial-keyword publish/subscribe has emerged as a very important framework to disseminate real-time messages (e.g., geo-tagged e-coupon) to registered subscriptions (e.g., users interested in nearby promotions). While there are several work focusing on improving the efficiency of spatial-keyword publish/subscribe, their techniques fail to consider both the spatial and keyword distributions in a fine manner, thus lacking of scalability when coping with massive subscriptions. In this demonstration, we propose SKPS, a centralized in-memory spatial-keyword publish/ subscribe system, which exploits fully the spatial and keyword distributions of subscription workload during indexing construction, and employs an efficient message matching algorithm to disseminate each incoming message to relevant subscriptions in a real-time manner. We present a prototype of SKPS which provides users with a web-based interface to explore the message dissemination in publish/subscribe system.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-319-46922-5_36	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	SKPS: Towards efficient processing of spatial-keyword publish/subscribe system	en_US
dc.type	Conference Proceeding
utslib.citation.volume	9877 LNCS	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	9877 LNCS	en_US

Abstract:

© Springer International Publishing AG 2016. With the popularity of geo-equipped devices and location based services, spatial-keyword publish/subscribe has emerged as a very important framework to disseminate real-time messages (e.g., geo-tagged e-coupon) to registered subscriptions (e.g., users interested in nearby promotions). While there are several work focusing on improving the efficiency of spatial-keyword publish/subscribe, their techniques fail to consider both the spatial and keyword distributions in a fine manner, thus lacking of scalability when coping with massive subscriptions. In this demonstration, we propose SKPS, a centralized in-memory spatial-keyword publish/ subscribe system, which exploits fully the spatial and keyword distributions of subscription workload during indexing construction, and employs an efficient message matching algorithm to disseminate each incoming message to relevant subscriptions in a real-time manner. We present a prototype of SKPS which provides users with a web-based interface to explore the message dissemination in publish/subscribe system.

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http://hdl.handle.net/10453/101307