![](/images/graphics-bg.png)
An Activation Method of Topic Dictionary to Expand Training Data for Trend Rule Discovery
Joint Authors
Sakurai, Shigeaki
Matsumoto, Shigeru
Makino, Kyoko
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-26
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Abstract EN
This paper improves a method which predicts whether evaluation objects such as companies and products are to be attractive in near future.
The attractiveness is evaluated by trend rules.
The trend rules represent relationships among evaluation objects, keywords, and numerical changes related to the evaluation objects.
They are inductively acquired from text sequential data and numerical sequential data.
The method assigns evaluation objects to the text sequential data by activating a topic dictionary.
The dictionary describes keywords representing the numerical change.
It can expand the amount of the training data.
It is anticipated that the expansion leads to the acquisition of more valid trend rules.
This paper applies the method to a task which predicts attractive stock brands based on both news headlines and stock price sequences.
It shows that the method can improve the detection performance of evaluation objects through numerical experiments.
American Psychological Association (APA)
Sakurai, Shigeaki& Makino, Kyoko& Matsumoto, Shigeru. 2014. An Activation Method of Topic Dictionary to Expand Training Data for Trend Rule Discovery. Applied Computational Intelligence and Soft Computing،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-505015
Modern Language Association (MLA)
Sakurai, Shigeaki…[et al.]. An Activation Method of Topic Dictionary to Expand Training Data for Trend Rule Discovery. Applied Computational Intelligence and Soft Computing No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-505015
American Medical Association (AMA)
Sakurai, Shigeaki& Makino, Kyoko& Matsumoto, Shigeru. An Activation Method of Topic Dictionary to Expand Training Data for Trend Rule Discovery. Applied Computational Intelligence and Soft Computing. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-505015
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-505015