DSKQ: A system for efficient processing of diversified spatial-keyword query

Jiang, S; Zhang, C; Zhang, Y; Zhang, W; Lin, X; Cheema, MA; Wang, X

DSKQ: A system for efficient processing of diversified spatial-keyword query

Jiang, S Zhang, C Zhang, Y

Zhang, W

Lin, X

Cheema, MA Wang, X

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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), 2017, 10538 LNCS pp. 280 - 284
Issue Date:: 2017-01-01

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Field	Value	Language
dc.contributor.author	Jiang, S	en_US
dc.contributor.author	Zhang, C	en_US
dc.contributor.author	Zhang, Y https://orcid.org/0000-0002-2674-1638	en_US
dc.contributor.author	Zhang, W https://orcid.org/0000-0001-6572-2600	en_US
dc.contributor.author	Lin, X https://orcid.org/0000-0003-2396-7225	en_US
dc.contributor.author	Cheema, MA	en_US
dc.contributor.author	Wang, X	en_US
dc.date.issued	2017-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, 10538 LNCS pp. 280 - 284	en_US
dc.identifier.isbn	9783319681542	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/127690
dc.description.abstract	© 2017, Springer International Publishing AG. With the rapid development of mobile portable devices and location positioning technologies, massive amount of geo-textual data are being generated by a huge number of web users on various social platforms, such as Facebook and Twitter. Meanwhile, spatial-textual objects that represent Point-of-interests (POIs, e.g., shops, cinema, hotel or restaurant) are increasing pervasively. Consequently, how to retrieve a set of objects that best matches the user’s submitted spatial keyword query (SKQ) has been intensively studied by the research communities and commercial organisations. Existing works only focus on returning the nearest matching objects, although we observe that many real-life applications are now using diversification to enhance the quality of the query results. Thus, existing methods fail to solve the problem of diversified SKQ efficiently. In this demonstration, we introduce DSKQ, a diversified in-memory spatial-keyword query system, which considers both the textual relevance and the spatial diversity of the results processing on road network. We present a prototype of DSKQ which provides users with an application-based interface to explore the diversified spatial-keyword query 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	10.1007/978-3-319-68155-9_22	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	DSKQ: A system for efficient processing of diversified spatial-keyword query	en_US
dc.type	Conference Proceeding
utslib.citation.volume	10538 LNCS	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	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/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	10538 LNCS	en_US

Abstract:

© 2017, Springer International Publishing AG. With the rapid development of mobile portable devices and location positioning technologies, massive amount of geo-textual data are being generated by a huge number of web users on various social platforms, such as Facebook and Twitter. Meanwhile, spatial-textual objects that represent Point-of-interests (POIs, e.g., shops, cinema, hotel or restaurant) are increasing pervasively. Consequently, how to retrieve a set of objects that best matches the user’s submitted spatial keyword query (SKQ) has been intensively studied by the research communities and commercial organisations. Existing works only focus on returning the nearest matching objects, although we observe that many real-life applications are now using diversification to enhance the quality of the query results. Thus, existing methods fail to solve the problem of diversified SKQ efficiently. In this demonstration, we introduce DSKQ, a diversified in-memory spatial-keyword query system, which considers both the textual relevance and the spatial diversity of the results processing on road network. We present a prototype of DSKQ which provides users with an application-based interface to explore the diversified spatial-keyword query system.

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http://hdl.handle.net/10453/127690