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

2015 | OriginalPaper | Chapter

Temporal PageRank on Social Networks

Authors : Weishu Hu, Haitao Zou, Zhiguo Gong

Published in: Web Information Systems Engineering – WISE 2015

Publisher: Springer International Publishing

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Abstract

Social network has been a widely accepted way for people to communicate and interact online. However, few of existing works studied temporal dimension in assessing the authority of nodes on social networks. In this paper, a novel Temporal PageRank (T-PR) algorithm is proposed for analyzing the authority of nodes. Three temporal factors are adopted to personalize PageRank, which favors the nodes that are more important to people. They are Built-up Time-length Factor (BTF), Frequency Factor (FF), and Similarity Factor (SF). The experiments on a real data set demonstrate T-PR algorithm provides the best ranking results over recent competitor methods.

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Metadata
Title
Temporal PageRank on Social Networks
Authors
Weishu Hu
Haitao Zou
Zhiguo Gong
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_18

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