Show simple item record

dc.contributor.authorXu, Ying
dc.contributor.authorChen, Lisi
dc.contributor.authorYao, Bin
dc.contributor.authorShang, Shuo
dc.contributor.authorZhu, Shunzhi
dc.contributor.authorZheng, Kai
dc.contributor.authorLi, Fang
dc.date.accessioned2017-10-25T10:50:26Z
dc.date.available2017-10-25T10:50:26Z
dc.date.issued2017-10-03
dc.identifier.citationXu Y, Chen L, Yao B, Shang S, Zhu S, et al. (2017) Location-Based Top-k Term Querying over Sliding Window. Web Information Systems Engineering – WISE 2017: 299–314. Available: http://dx.doi.org/10.1007/978-3-319-68783-4_21.
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.doi10.1007/978-3-319-68783-4_21
dc.identifier.urihttp://hdl.handle.net/10754/625945
dc.description.abstractIn part due to the proliferation of GPS-equipped mobile devices, massive svolumes of geo-tagged streaming text messages are becoming available on social media. It is of great interest to discover most frequent nearby terms from such tremendous stream data. In this paper, we present novel indexing, updating, and query processing techniques that are capable of discovering top-k locally popular nearby terms over a sliding window. Specifically, given a query location and a set of geo-tagged messages within a sliding window, we study the problem of searching for the top-k terms by considering both the term frequency and the proximities between the messages containing the term and the query location. We develop a novel and efficient mechanism to solve the problem, including a quad-tree based indexing structure, indexing update technique, and a best-first based searching algorithm. An empirical study is conducted to show that our proposed techniques are efficient and fit for users’ requirements through varying a number of parameters.
dc.description.sponsorshipThis work was supported by the NSFC (U1636210, 61373156, 91438121 and 61672351), the National Basic Research Program (973 Program, No. 2015CB352403), the National Key Research and Development Program of China (2016YFB0700502), the Scientific Innovation Act of STCSM (15JC1402400) and the Microsoft Research Asia.
dc.publisherSpringer Nature
dc.relation.urlhttps://link.springer.com/chapter/10.1007%2F978-3-319-68783-4_21
dc.rightsThe final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-68783-4_21
dc.subjectLocation
dc.subjectTerm
dc.subjectTop-k
dc.titleLocation-Based Top-k Term Querying over Sliding Window
dc.typeBook Chapter
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalWeb Information Systems Engineering – WISE 2017
dc.conference.date2017-10-07 to 2017-10-11
dc.conference.name18th International Conference on Web Information Systems Engineering, WISE 2017
dc.conference.locationPuschino, RUS
dc.eprint.versionPost-print
dc.contributor.institutionShanghai Jiao Tong University, Shanghai, , China
dc.contributor.institutionHong Kong Baptist University, , Hong Kong
dc.contributor.institutionXiamen University of Technology, Xiamen, , China
dc.contributor.institutionSoochow University, Soochow, , China
kaust.personShang, Shuo


Files in this item

Thumbnail
Name:
wise201787.pdf
Size:
1.019Mb
Format:
PDF
Description:
Accepted Manuscript

This item appears in the following Collection(s)

Show simple item record