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    题名: 應用情感分析於產品比較與品牌推薦系統-以美妝產品為例
    Application of Sentiment Analysis in Product Comparison and Brand Recommendation System - Taking Cosmetics as an Example
    作者: 俞舒禔
    Yu, Shu-Ti
    贡献者: 鄭宇庭
    郭訓志
    Cheng , Yu Ting
    Kuo , Hsun Chih
    俞舒禔
    Yu, Shu-Ti
    关键词: 文字探勘
    Word2vec
    CRF
    PMI
    情感分析
    日期: 2018
    上传时间: 2018-06-01 17:34:45 (UTC+8)
    摘要: 近年來，社群商業智慧（SBI, Social Business Intelligence）興盛，且IBM公司指出「在現今社會當中早已不再是B to B（企業對企業）或是B to C（企業對客戶）的關係，而是P to P（人對人）」，多數企業看準了P to P消費者互動模式之繁榮而從中衍生出龐大商機。因此本研究欲藉由三大美妝評論網站蒐集之文字資料進行文字探勘，將非結構化資料轉為結構化資料後，利用字典比對法搭配機器學習方法，自定義詞典後透過Google於2013年開源之Word2vec深度學習方法擴建辭典，接著透過CRF詞性辨識方法建模，用以辨識出形容詞與屬性詞，以便後續進行PMI相似性比對，此法可大幅降低自然語言處理在分析上的人工作業時間，本研究在情感分析上設計一套專屬於美妝產品情感取向之算分方式且對文章進行分類（正面、中性、負面），所建構之情感取向辨識系統預測文章之準確率約為78 %；本研究之另一研究為利用統計方法將單篇美妝文章對於各屬性辭典（顏色、味道、效果、價格）給予星等。從消費者角度出發，消費者可透過選定之品牌以及產品畫出雷達圖進行比較，進而得知自家美妝產品以及他牌美妝產品的優缺點，透過顏色、味道、效果以及價錢上的平均星等數，可以迅速得知哪一品牌的美妝產品較受美妝部落客以及廣大網路評論者的歡迎；從美妝品牌公司角度出發，若在某項屬性之平均星等數與他牌有所差距，可自我檢討並改進，若在某屬性有較高的平均星等數，可維持其優良的部分並提升自家美妝產品的競爭力。
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    描述: 碩士
    國立政治大學
    統計學系
    105354006
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G1053540061
    数据类型: thesis
    显示于类别:[統計學系] 學位論文

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