JSW 2013 Vol.8(3): 737-745 ISSN: 1796-217X
doi: 10.4304/jsw.8.3.737-745
doi: 10.4304/jsw.8.3.737-745
A System for Extracting and Ranking Name Aliases in Emails
Yin Meijuan1, Liu Xiaonan1, Luo Junyong1, Luo Xiangyang1, 2
1Zhengzhou Information Science and Technology Institute, Zhengzhou 450002, China
2State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093
Abstract—Mining potential information about person identity in emails is one of the popular research topics in email mining. This paper focuses on mining name aliases of a user from emails. Firstly, a system for extracting and ranking name aliases is proposed, which includes two modules: the Alias Extraction Module and the Alias Authority Ranking Module. Secondly, the methods used in the Alias Authority Ranking Module to rank the authority of name aliases of a user are presented in detail, which are based on email communication relation analysis and morphologically similar alias clustering. At last, we evaluate the proposed methods on the public subset of the Enron corpus. Experiment results show that the proposed system can efficiently extract name aliases and find the authoritative aliases of a user.
Index Terms—Email mining, Name alias extraction, Alias authority ranking, Email communication relation analysis, Morphologically similar alias clustering.
2State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093
Abstract—Mining potential information about person identity in emails is one of the popular research topics in email mining. This paper focuses on mining name aliases of a user from emails. Firstly, a system for extracting and ranking name aliases is proposed, which includes two modules: the Alias Extraction Module and the Alias Authority Ranking Module. Secondly, the methods used in the Alias Authority Ranking Module to rank the authority of name aliases of a user are presented in detail, which are based on email communication relation analysis and morphologically similar alias clustering. At last, we evaluate the proposed methods on the public subset of the Enron corpus. Experiment results show that the proposed system can efficiently extract name aliases and find the authoritative aliases of a user.
Index Terms—Email mining, Name alias extraction, Alias authority ranking, Email communication relation analysis, Morphologically similar alias clustering.
Cite: Yin Meijuan, Liu Xiaonan, Luo Junyong, Luo Xiangyang, "A System for Extracting and Ranking Name Aliases in Emails," Journal of Software vol. 8, no. 3, pp. 737-745, 2013.
General Information
ISSN: 1796-217X (Online)
Frequency: Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKI, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
-
Apr 26, 2021 News!
Vol 14, No 4- Vol 14, No 12 has been indexed by IET-(Inspec) [Click]
-
Nov 18, 2021 News!
Papers published in JSW Vol 16, No 1- Vol 16, No 6 have been indexed by DBLP [Click]
-
Dec 24, 2021 News!
Vol 15, No 1- Vol 15, No 6 has been indexed by IET-(Inspec) [Click]
-
Nov 18, 2021 News!
[CFP] 2022 the annual meeting of JSW Editorial Board, ICCSM 2022, will be held in Rome, Italy, July 21-23, 2022 [Click]
-
Aug 01, 2023 News!