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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 李瑞庭 | |
dc.contributor.author | Chao-Hung Chen | en |
dc.contributor.author | 陳昭宏 | zh_TW |
dc.date.accessioned | 2021-06-16T13:05:04Z | - |
dc.date.available | 2018-08-28 | |
dc.date.copyright | 2013-08-28 | |
dc.date.issued | 2013 | |
dc.date.submitted | 2013-08-05 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/61529 | - |
dc.description.abstract | 顧客評論是公司珍貴的資源,因為顧客常分享他們的使用經驗並對各產品特徵提供有用的意見。因此,在這篇論文中,我們提出一個MPM(Mining Perceptual Map)的方法,自動地從顧客評論中建構知覺定位圖與雷達圖,知覺定位圖與雷達圖都是廣泛應用於行銷與商業分析中的視覺化工具。從大量的顧客評論中,建構知覺定位圖與雷達圖,可以降低個人主觀的偏見。本實驗結果可提供智慧型手機業者一些實用的觀察與建議,我們提出的方法可幫助公司定位其產品並制定有效的競爭策略。 | zh_TW |
dc.description.abstract | Consumer reviews are valuable resources for companies since consumers usually share their using experiences on the product or provide useful opinions from various aspects such as different product features. Therefore, in this thesis, we propose a method called MPM (Mining Perceptual Map) to automatically build perceptual maps and radar charts from consumer reviews. Perceptual maps and radar charts are business tools widely used in marketing and business analysis. The proposed method may reduce subjective personal bias since perceptual maps and radar charts are mined from a large number of consumer reviews. The experimental results may provide some practical insight for smartphone companies. Our method can help firms to position new products, and formulate effective marketing and competitive strategies. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T13:05:04Z (GMT). No. of bitstreams: 1 ntu-102-R00725002-1.pdf: 2012534 bytes, checksum: 70c472adc58509686f65832ea806853c (MD5) Previous issue date: 2013 | en |
dc.description.tableofcontents | List of Figures vii
List of Tables viii Chapter 1 Introduction 1 Chapter 2 Related Work 5 2.1 Clustering product features 5 2.2 Building perceptual maps and radar charts 7 2.3 Sentiment analysis 7 Chapter 3 Preliminary Concepts and Problem Definitions 9 Chapter 4 The Proposed Method 11 4.1 Extracting product features 11 4.2 Building a virtual document for each product feature 11 4.3 Clustering product features 13 4.4 Pruning redundant product features 15 4.5 Building perceptual maps and radar charts 16 Chapter 5 Experimental Results 18 5.1 Datasets 18 5.2 Performance of clustering product features 19 5.3 Perceptual map 22 5.3.1 By brand 22 5.3.2 By price 26 Chapter 6 Conclusions and Future Work 29 References 31 | |
dc.language.iso | en | |
dc.title | 從顧客評論探勘知覺定位圖 | zh_TW |
dc.title | Mining Perceptual Maps from Consumer Reviews | en |
dc.type | Thesis | |
dc.date.schoolyear | 101-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 陳彥良,劉敦仁 | |
dc.subject.keyword | 情感分析,意見探勘,隱含狄利克雷分佈,知覺定位圖,雷達圖, | zh_TW |
dc.subject.keyword | sentiment analysis,opinion mining,Latent Dirichlet Allocation,perceptual maps,radar charts, | en |
dc.relation.page | 33 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2013-08-05 | |
dc.contributor.author-college | 管理學院 | zh_TW |
dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
顯示於系所單位: | 資訊管理學系 |
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