Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/105673
Title: A system for region search and exploration
Authors: Feng, Kaiyu
Zhao, Kaiqi
Liu, Yiding
Cong, Gao
Keywords: Engineering::Computer science and engineering
Region Search
Timespan
Issue Date: 2016
Source: Feng, K., Zhao, K., Liu, Y., & Cong, G. (2016). A system for region search and exploration. Proceedings of the VLDB Endowment, 9(13), 1549-1552.
Series/Report no.: Proceedings of the VLDB Endowment
Abstract: With the increasing popularity of mobile devices and location based services, massive amount of geo-textual data (e.g., geo-tagged tweets) is being generated everyday. Compared with traditional spatial data, the textual dimension of geo-textual data greatly enriches the data. Meanwhile, the spatial dimension of geo-textual data also adds a semantically rich new aspect to textual data. The large volume, together with its rich semantics, calls for the need for data exploration. First, it has many applications to retrieve a region for exploration that satisfies user-specified conditions (e.g., the size and shape of the region) while maximizing some other conditions (e.g., the relevance to the query keywords of the objects in the region). Second, it is useful to mine and explore the topics of the geo-textual data within a (specified or retrieved) region and perhaps a timespan. This demonstration proposal presents the main ideas of our system, the RegIon Search and Exploration System (RISE), for efficiently supporting region search and exploration, and our demonstration plan.
URI: https://hdl.handle.net/10356/105673
http://hdl.handle.net/10220/49541
ISSN: 2150-8097
Rights: © 2016 VLDB Endowment. This work is licensed under the Creative Commons AttributionNonCommercial-NoDerivatives 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. For any use beyond those covered by this license, obtain permission by emailing info@vldb.org.
metadata.item.grantfulltext: open
metadata.item.fulltext: With Fulltext
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