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Issue title: Granular Knowledge Discovery
Guest editors: Dominik Ślȩzak, Andrzej Skowron, Yukio Ohsawa and Junzo Watada
Article type: Research Article
Authors: Takama, Yasufumi* | Okumura, Masaki
Affiliations: Graduate School of System Design, Tokyo Metropolitan University, Hino, Tokyo, Japan
Correspondence: [*] Corresponding author: Yasufumi Takama, Graduate School of System Design, Tokyo Metropolitan University, 6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan. Tel./Fax: +81 42 585 8629; E-mail:ytakama@tmu.ac.jp
Abstract: This paper proposes an interactive visualization system that supports tasks of monitoring multiple BBS threads. A BBS is one of important resources about the latest information and wide range of opinions about various topics. However, we must spend much time on reading large number of posts in several threads to recognize discussed topics. Furthermore, a monitoring support system should be designed considering characteristics specific to monitoring task. That is, it should be done during breaks of our primary jobs. The proposed system employs keyword-based visualization, and a user can track various topics by selecting keywords of interest. In order to provide users with keywords reflecting topics and those giving details about topics, two types of keywords are extracted. Those are tracking candidates and detailed keywords, which are extracted with different measures. Furthermore, the system employs multiple views for displaying topics about multiple threads and focused thread at the same time. Experiments are conducted with test participants, of which the results show the system can provide various keywords with different granularities. It is also shown that participants checked topics of interest by using the provided information as a clue for selecting keywords.
Keywords: Information visualization, monitoring support, text stream data, BBS
DOI: 10.3233/IDT-140232
Journal: Intelligent Decision Technologies, vol. 9, no. 4, pp. 391-403, 2015
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