Simultaneously finding fundamental articles and new topics using a community tracking method

Tieyun Qian, Jaideep Srivastava, Zhiyong Peng, Phillip C Y Sheu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

In this paper, we study the relationship between fundamental articles and new topics and present a new method to detect recently formed topics and its typical articles simultaneously. Based on community partition, the proposed method first identifies the emergence of a new theme by tracking the change of the community where the top cited nodes lie. Next, the paper with a high citation number belonging to this new topic is recognized as a fundamental article. Experimental results on real dataset show that our method can detect new topics with only a subset of data in a timely manner, and the identified papers for these topics are found to have a long lifespan and keep receiving citations in the future.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages796-803
Number of pages8
Volume5476 LNAI
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event13th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2009 - Bangkok
Duration: 27 Apr 200930 Apr 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5476 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other13th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2009
CityBangkok
Period27/4/0930/4/09

Fingerprint

Citations
Life Span
Partition
Subset
Experimental Results
Vertex of a graph
Community
Relationships

Keywords

  • Community tracking
  • Fundamental article finding
  • New topic identification

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Qian, T., Srivastava, J., Peng, Z., & Sheu, P. C. Y. (2009). Simultaneously finding fundamental articles and new topics using a community tracking method. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5476 LNAI, pp. 796-803). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5476 LNAI). https://doi.org/10.1007/978-3-642-01307-2_82

Simultaneously finding fundamental articles and new topics using a community tracking method. / Qian, Tieyun; Srivastava, Jaideep; Peng, Zhiyong; Sheu, Phillip C Y.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5476 LNAI 2009. p. 796-803 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5476 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Qian, T, Srivastava, J, Peng, Z & Sheu, PCY 2009, Simultaneously finding fundamental articles and new topics using a community tracking method. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 5476 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5476 LNAI, pp. 796-803, 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2009, Bangkok, 27/4/09. https://doi.org/10.1007/978-3-642-01307-2_82
Qian T, Srivastava J, Peng Z, Sheu PCY. Simultaneously finding fundamental articles and new topics using a community tracking method. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5476 LNAI. 2009. p. 796-803. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-01307-2_82
Qian, Tieyun ; Srivastava, Jaideep ; Peng, Zhiyong ; Sheu, Phillip C Y. / Simultaneously finding fundamental articles and new topics using a community tracking method. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5476 LNAI 2009. pp. 796-803 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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