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Grouping Product Aspects from Short Texts Using Multiple Classifiers Read chapter Read first chapter

2015 | OriginalPaper | Chapter

An Efficient Location-Aware Publish/Subscribe Index with Boolean Expressions

Authors : Hanhan Jiang, Pengpeng Zhao, Victor S. Sheng, Guanfeng Liu, An Liu, Jian Wu, Zhiming Cui

Published in: Web Information Systems Engineering – WISE 2015

Publisher: Springer International Publishing

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Abstract

A location-aware publish/subscribe (pub/sub) system is gaining more and more interest in both industry and academia with the rapid progress of mobile Internet and the rising popularity of smart-phones. Nowadays, with the booming of E-commerce, Object-to-Object (OTO) services are gaining more and more popularity, which results in millions of products with different structured descriptions and locations. To meet this requirement, a pub/sub system should handle subscriptions with location-aware boolean expressions to present users’ interests. In this paper, we propose an efficient location-aware pub/sub index for boolean expressions, called RP-trees. RP-trees integrates an R-tree index and a boolean expression index together, can efficiently and simultaneously prune boolean expressions and spatial dimensions. Our experimental results show that RP-trees achieves better performance on both a synthetic dataset and a real-world dataset.

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Footnotes
Literature
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Metadata
Title
An Efficient Location-Aware Publish/Subscribe Index with Boolean Expressions
Authors
Hanhan Jiang
Pengpeng Zhao
Victor S. Sheng
Guanfeng Liu
An Liu
Jian Wu
Zhiming Cui
Copyright Year
2015
Book
Web Information Systems Engineering – WISE 2015

Print ISBN: 978-3-319-26189-8

Electronic ISBN: 978-3-319-26190-4

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-26190-4_15

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