Presentation 2015-09-10
Research Information Mining
Osamu Segawa,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) We have investigated a possibility of utilization on academic paper archives as big data (knowledge resource). In this paper, we describe several methods of our research information mining technique for trend forecastand creativity support, for example, technical topic analysis, network analysis, causal analysis, keyword association, and show their evaluation results.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Text mining / Academic paper / Topic analysis / Network analysis / Causal analysis / Keyword association
Paper # NLC2015-20
Date of Issue 2015-09-03 (NLC)

Conference Information
Committee NLC
Conference Date 2015/9/10(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Convention Room AP Shibuya-Dogenzaka (Tokyo)
Topics (in Japanese) (See Japanese page)
Topics (in English) The Seventh Text Mining Symposium
Chair Koichi Takeuchi(Okayama Univ.)
Vice Chair Hiroshi Kanayama(IBM) / Makoto Ichise(NTT DoCoMo)
Secretary Hiroshi Kanayama(Univ. of Tokyo/Hottolink) / Makoto Ichise(Ryukoku Univ.)
Assistant Kazutaka Shimada(Kyushu Inst. of Tech.) / Ryuichiro Higashinaka(NTT)

Paper Information
Registration To Technical Committee on Natural Language Understanding and Models of Communication
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Research Information Mining
Sub Title (in English) Utilization of Academic Paper Archives as Big Data
Keyword(1) Text mining
Keyword(2) Academic paper
Keyword(3) Topic analysis
Keyword(4) Network analysis
Keyword(5) Causal analysis
Keyword(6) Keyword association
1st Author's Name Osamu Segawa
1st Author's Affiliation Chubu Electric Power Co., Inc.(CEPCO)
Date 2015-09-10
Paper # NLC2015-20
Volume (vol) vol.115
Number (no) NLC-222
Page pp.pp.19-24(NLC),
#Pages 6
Date of Issue 2015-09-03 (NLC)