政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/120379
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113648/144635 (79%)
Visitors : 51618999      Online Users : 566
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/120379


    Title: Opinion Mining for Multiple Types of Emotion-Embedded Products/Services through Evolution Strategy
    Authors: Yang, Heng-Li;Lin, Qing-Feng
    楊亨利
    Yang, Heng-Li
    Contributors: 資管系
    Keywords: Chinese corpus;Evolutionary strategy;Multiple polarities;Opinion mining;Optimization;Sentiment analysis
    Date: 2018-06
    Issue Date: 2018-10-05 16:31:04 (UTC+8)
    Abstract: Since the advent of blogging, microblogging, and social networking sites, researchers and practitioners have been increasingly concerned with the problem of obtaining useful evaluations from web-based opinion articles in a process known as opinion mining or sentiment analysis. In this study, we focused on reviews based on highly emotion-embedded products/services, such as movies, music, and drama. Furthermore, we tried to solve the multiple polarities problem for the same review word for multiple types of product/service. First, we collected text written in Chinese from a Taiwanese movie forum. In our proposed approach, we applied an evolutionary strategy algorithm to optimize the weight tables corresponding to two different types of movies: horror and drama movies. The experimental results indicated that the proposed method performed better than conventional methods when considering only one generalized type. Further, we employed a new multi-class support vector machine approach for predicting opinions at the document level. We used seven measures to describe the characteristics of an overall document, including the central tendency, dispersion, and shape of the predicted sentence value distribution, where the fluctuations in these values corresponded to their positions in the document. We also demonstrated the effectiveness of this approach for identifying opinions at the document level.
    Relation: Expert Systems with Applications, Vol.99, pp.44-55
    Data Type: article
    DOI link: https://doi.org/10.1016/j.eswa.2018.01.022
    DOI: 10.1016/j.eswa.2018.01.022
    Appears in Collections:[Department of MIS] Periodical Articles

    Files in This Item:

    File Description SizeFormat
    4455.pdf930KbAdobe PDF2404View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback