Presentation 2017-02-09
Stock market prediction from Web news using expert articles and machine learning
Ko Ichinose, Kazutaka Shimada,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) The market analysis is one of the important tasks for text mining. Many researchers have proposed methods using text information for analyzing the market. In this situation, Web news has an important role to predict stock prices. In this paper, we propose a method to predict the Nikkei Stock Average, which is one of the most important stock market indexes. We extract viewpoints for analyzing web-news from analysis's articles of an expert and apply the viewpoints and a machine learning technique into the method. Then, we classify the next day into “UP” or “DOWN” by using the articles of a day. The experimental result shows the effectiveness of extracting viewpoints from expert articles.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Stock price prediction / SVM / Text mining / Expert articles
Paper # NLC2016-43
Date of Issue 2017-02-02 (NLC)

Conference Information
Committee NLC / IPSJ-IFAT
Conference Date 2017/2/9(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Hiroshi Kanayama(IBM)
Vice Chair Makoto Ichise(NTT DoCoMo) / Takeshi Sakaki(Univ. of Tokyo/Hottolink)
Secretary Makoto Ichise(Ryukoku Univ.) / Takeshi Sakaki(Kyushu Inst. of Tech.)
Assistant Ryuichiro Higashinaka(NTT) / Mitsuo Yoshida(Toyohashi Univ. of Tech.)

Paper Information
Registration To Technical Committee on Natural Language Understanding and Models of Communication / Special Interest Group on Information Fundamentals and Access Technologies
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Stock market prediction from Web news using expert articles and machine learning
Sub Title (in English)
Keyword(1) Stock price prediction
Keyword(2) SVM
Keyword(3) Text mining
Keyword(4) Expert articles
1st Author's Name Ko Ichinose
1st Author's Affiliation Kyushu Institute of Technology(KIT)
2nd Author's Name Kazutaka Shimada
2nd Author's Affiliation Kyushu Institute of Technology(KIT)
Date 2017-02-09
Paper # NLC2016-43
Volume (vol) vol.116
Number (no) NLC-451
Page pp.pp.19-24(NLC),
#Pages 6
Date of Issue 2017-02-02 (NLC)