A Hybrid On-line Topic Groups Mining Platform

Cheng-Lin Yang*, Yun-Heh Chen-Burger

*Corresponding author for this work

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

Abstract

In recent years, there is a rapid increased use of social networking platforms in the forms of short-text communication. Such communication can be indicative to popular public opinions and may be influential to real-life events. It is worth to identify topic groups from it automatically so it can help the analyst to understand the social network easily. However, due to the short-length of the texts used, the precise meaning and context of such texts are often ambiguous. In this paper, we proposed a hybrid framework, which adapts and extends the text clustering technique that uses Wikipedia as background knowledge. Based on this method, we are able to achieve higher level of precision in identifying the group of messages that has the similar topic.

Original languageEnglish
Title of host publicationAgent and Multi-Agent Systems: Technologies and Applications
Subtitle of host publication9th KES International Conference, KES-AMSTA 2015 Sorrento, Italy, June 2015, Proceedings
EditorsGordon Jezic, Robert J. Howlett, Lakhmi C. Jain
PublisherSpringer
Pages205-215
Number of pages11
VolumePart IV
ISBN (Electronic)978-3-319-19728-9
ISBN (Print)978-3-319-19727-2
DOIs
Publication statusPublished - 2015
Event9th International KES Conference on Agents and Multi-Agent Systems: Technologies and Applications - Sorrento, Italy
Duration: 17 Jun 201519 Jun 2015

Publication series

NameSmart Innovation Systems and Technologies
PublisherSpringer International Publishing
Volume38
ISSN (Print)2190-3018

Conference

Conference9th International KES Conference on Agents and Multi-Agent Systems: Technologies and Applications
Abbreviated titleKES-AMSTA 15
Country/TerritoryItaly
CitySorrento
Period17/06/1519/06/15

Keywords

  • Social Network Analysis
  • Micro-blogging System
  • Machine Learning

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