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https://hdl.handle.net/10356/104998
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DC Field | Value | Language |
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dc.contributor.author | Chen, Lisi | en_US |
dc.contributor.author | Cui, Yan | en_US |
dc.contributor.author | Cong, Gao | en_US |
dc.contributor.author | Cao, Xin | en_US |
dc.date.accessioned | 2014-08-28T07:30:49Z | en |
dc.date.accessioned | 2019-12-06T21:44:18Z | - |
dc.date.available | 2014-08-28T07:30:49Z | en |
dc.date.available | 2019-12-06T21:44:18Z | - |
dc.date.copyright | 2014 | en |
dc.date.issued | 2014 | - |
dc.identifier.citation | 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 | en |
dc.identifier.uri | https://hdl.handle.net/10356/104998 | - |
dc.description.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. | en_US |
dc.format.extent | 4 p. | en |
dc.language.iso | en | en_US |
dc.relation.ispartofseries | Proceedings of the VLDB endowment | en |
dc.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. | en_US |
dc.subject | DRNTU::Engineering::Computer science and engineering | en_US |
dc.title | SOPS : a system for efficient processing of spatial-keyword publish/subscribe | en_US |
dc.type | Journal Article | en |
dc.contributor.school | School of Computer Engineering | en_US |
dc.identifier.doi | 10.14778/2733004.2733040 | - |
dc.description.version | Published version | en_US |
dc.identifier.url | http://www.vldb.org/2014/program/papers/demo/p1077-chen.pdf | en |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
Appears in Collections: | SCSE Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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SOPS a system for efficient processing of spatial-keyword publishsubscribe.pdf | 555.42 kB | Adobe PDF | View/Open |
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