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Inventi Impact: Soft Computing

Articles

  • Inventi:esc/68/14
    AN ACTIVATION METHOD OF TOPIC DICTIONARY TO EXPAND TRAINING DATA FOR TREND RULE DISCOVERY
    30-Jun-2014 Research 2014 : July - September
    Shigeaki Sakurai, Kyoko Makino, Shigeru Matsumoto

    This paper improves amethodwhich predictswhether evaluation objects such as companies and products are to be attractive in near\nfuture.The attractiveness is evaluated by trend rules. The trend rules represent relationships among evaluation objects, keywords,\nand numerical changes related to the evaluation objects. They are inductively acquired from text sequential data and numerical\nsequential data.The method assigns evaluation objects to the text sequential data by activating a topic dictionary.The dictionary\ndescribes keywords representing the numerical change. It can expand the amount of the training data. It is anticipated that the\nexpansion leads to the acquisition of more valid trend rules. This paper applies the method to a task which predicts attractive stock\nbrands based on both news headlines and stock price sequences. It shows that the method can improve the detection performance\nof evaluation objects through numerical experiments.

    How to Cite this Article
    CC Compliant Citation: Shigeaki Sakurai, Kyoko Makino, and\nShigeru Matsumoto, â??An Activation Method of Topic Dictionary\nto Expand Training Data for Trend Rule Discovery,â? Applied\nComputational Intelligence and Soft Computing, vol. 2014,\nArticle ID 871412, 11 pages, 2014. doi:10.1155/2014/871412.\n\nCopyright © 2014 Shigeaki Sakurai et al. This article is distributed under the Creative Commons Attribution License(http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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