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Sentence Compression with Reinforcement Learning Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Group Outlying Aspects Mining

Authors : Shaoni Wang, Haiyang Xia, Gang Li, Jianlong Tan

Published in: Knowledge Science, Engineering and Management

Publisher: Springer International Publishing

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Abstract

Existing works on outlying aspects mining have been focused on detecting the outlying aspects of a single query object, rather than the outlying aspects of a group of objects. While in many application scenarios, methods that can effectively mine the outlying aspects of a query group are needed. To fill this research gap, this paper extends the outlying aspects mining to the group level, and formalizes the problem of group outlying aspect mining. The Earth Move Distance based algorithm GOAM is then proposed to automatically identify the outlying aspects of the query group. The experiment result shows the capability of the proposed algorithm in identifying the group outlying aspects effectively.

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Metadata
Title
Group Outlying Aspects Mining
Authors
Shaoni Wang
Haiyang Xia
Gang Li
Jianlong Tan
Copyright Year
2018
Book
Knowledge Science, Engineering and Management

Print ISBN: 978-3-319-99364-5

Electronic ISBN: 978-3-319-99365-2

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-99365-2_18

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