English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 109948/140897 (78%)
Visitors : 46095308      Online Users : 855
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
    政大機構典藏 > 商學院 > 資訊管理學系 > 期刊論文 >  Item 140.119/133673


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/133673


    Title: 針對情感商品的推薦機制-以流行音樂為例
    Recommended Mechanism for Hedonic Products--Taking Pop Music as an Example
    Authors: 楊亨利
    Yang, Heng-Li
    林青峰
    Lin, Qing-Feng
    Contributors: 資管系
    Keywords: 情感分析 ; 流行音樂 ; 意見挖掘 ; 網路評論 ; 推薦規則 
    Sentiment analysis ; Pop music ; Opinion mining ; Internet review ; Recommendation mechanism
    Date: 2020-04
    Issue Date: 2021-01-22 09:22:18 (UTC+8)
    Abstract: 情感商品，如音樂、電影等，與一般單純為了使用功能的功能商品有很大的不同。因為情感商品的評價與個人感受有關，情感商品在網路上通常會存在比較多主觀的評論；商品的效用也更與商品本身內容及通常能帶給使用者什麼感覺與情緒來的有關。傳統上，對於網路評論，我們通常只關注評論中所述及的商品屬性，主要在找正負傾向規則，而不會去企圖找出像是「聽了讓人感到很遺憾」這種引發人類情緒的情感商品規則。本研究以流行音樂這個情感商品為例，提出一個針對情感商品的推薦機制。首先我們先建立能了解網路評論狀況的情感標籤分類器，用於隨時了解某商品目前網路評論的情感傾向；另外也建立一個同時考慮到音樂歌詞及音質特性的音樂內容分類器，用於從音樂的內容特徵來得到某音樂商品可能音樂情感傾向。經過資料的收集、分析與訓練，網路評論分類器與音樂內容分類器的精準率、召回率與F1均達令人滿意程度，進而本研究以實驗分析在用戶悲傷情緒下應推薦的音樂來說明情感商品的推薦規則建立過程。
    Purpose-This study aims to propose a mechanism based on web reviews opinion mining and product contents (e.g., audio and lyrics in our case) for hedonic product recommendation. Design/methodology/approach - The classifiers, web review SVM classifiers and music content SVM classifiers, were proposed and a prototype was also built. Finally, we designed an experiment for exemplifying the process of determining the recommended product when the user is in a particular mood. Findings-The acceptable precision, recall, F1 ratio were obtained for the two classifiers. The experiment indicated the recommendation rule while users are in sad mood. Research limitations/implications-We only take as an example of pop music. Other hedonic products (e.g., dancing) might be more complicated to analyze their contents owing to video. Practical implications-Following our proposed mechanism, the suppliers of hedonic products would know how to recommend proper contents to users to invoke their desirable feelings. Originality/value-The proposed mechanism is brand new. As we know, there is no such a recommended mechanism for hedonic product in literature.
    Relation: 資訊管理學報, 27:2, 175-204
    Data Type: article
    Appears in Collections:[資訊管理學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    433.pdf1322KbAdobe PDF2197View/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