English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 90773/120835 (75%)
Visitors : 25119059      Online Users : 277
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
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 商學院 > 資訊管理學系 > 期刊論文 >  Item 140.119/120379
    Please use this identifier to cite or link to this item: http://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
    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 連結: https://doi.org/10.1016/j.eswa.2018.01.022
    DOI: 10.1016/j.eswa.2018.01.022
    Appears in Collections:[資訊管理學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    4455.pdf930KbAdobe PDF188View/Open

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

    社群 sharing

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback