Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/104998
Title: SOPS : a system for efficient processing of spatial-keyword publish/subscribe
Authors: Chen, Lisi
Cui, Yan
Cong, Gao
Cao, Xin
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2014
Source: Chen, L., Cui, Y., Cong, G., & Cao, X. (2014). SOPS : a system for efficient processing of spatial-keyword publish/subscribe. Proceedings of the VLDB endowment, 7(13), 1601-1604. doi:10.14778/2733004.2733040
Series/Report no.: Proceedings of the VLDB endowment
Abstract: Massive amount of data that are geo-tagged and associated with text information are being generated at an unprecedented scale. These geo-textual data cover a wide range of topics. Users are interested in receiving up-to-date geo-textual objects (e.g., geo-tagged Tweets) such that their locations meet users' need and their texts are interesting to users. For example, a user may want to be updated with tweets near her home on the topic "dengue fever headache." In this demonstration, we present SOPS, the Spatial-Keyword Publish/Subscribe System, that is capable of efficiently processing spatial keyword continuous queries. SOPS supports two types of queries: (1) Boolean Range Continuous (BRC) query that can be used to subscribe the geo-textual objects satisfying a boolean keyword expression and falling in a specified spatial region; (2) Temporal Spatial-Keyword Top-k Continuous (TaSK) query that continuously maintains up-to-date top-k most relevant results over a stream of geo-textual objects. SOPS enables users to formulate their queries and view the real-time results over a stream of geotextual objects by browser-based user interfaces. On the server side, we propose solutions to efficiently processing a large number of BRC queries (tens of millions) and TaSK queries over a stream of geo-textual objects.
URI: https://hdl.handle.net/10356/104998
http://hdl.handle.net/10220/20434
DOI: 10.14778/2733004.2733040
Rights: © 2014 VLDB Endowment. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/. Obtain permission prior to any use beyond those covered by the license. Contact copyright holder by emailing info@vldb.org. Articles from this volume were invited to present their results at the 40th International Conference on Very Large Data Bases, September 1st - 5th 2014, Hangzhou, China.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

Files in This Item:
File Description SizeFormat 
SOPS a system for efficient processing of spatial-keyword publishsubscribe.pdf555.42 kBAdobe PDFThumbnail
View/Open

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.