博碩士論文 etd-0711103-093314 詳細資訊


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姓名 莊士民(Shih-Min Chuang) 電子郵件信箱 m9042639@student.nsysu.edu.tw
畢業系所 資訊管理學系研究所(Information Management)
畢業學位 碩士(Master) 畢業時期 91學年第2學期
論文名稱(中) 結合內容及合作推薦技術之文獻數位圖書館
論文名稱(英) Combining Content-based and Collaborative Article Recommendation in Literature Digital Libraries
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    統計 本論文已被瀏覽 5357 次,被下載 3699 次
    摘要(中) 文獻數位圖書館提供文獻數位化的儲存,研究人員可以透過網路很方便地使用文獻的查詢。然而在查詢文獻的時候,往往一次的查詢會得到相當大量的文獻列表,然而其中真正研究人員有興趣的可能只有極少部分。為了提供更有效率的查詢服務,愈來愈多系統提供推薦服務。系統根據使用統計和使用者的查詢記錄來推薦過去常常一起被瀏覽的文獻,或者是內容相似度高的文獻。文獻推薦系統和傳統推薦系統最主要的不同在於只有瀏覽紀錄而無評比分數,也就是沒有負項的評分作為資訊。
    本研究改進合作推薦(Collaborative recommendation)最主要的問題,也就是能夠推薦的文獻佔整體的比率不高。在方法上,首先提出三種利用內容導向過濾(Content-Based Filtering)的方式來推薦,另外提出混和內容導向和合作推薦的合併方式二種。在評估的部分,則是用中山大學學位論文系統的Web log中,找出代表使用者行為的transaction來評估推薦方法的precision、recall,與執行時間。結果發現合併推薦的方式整體而言會有較好的推薦結果。
    摘要(英) Literature digital libraries are the source of digitalized literature data, from which Researchers can search for articles that meet their personal interest. However, Users often confused by the large number of articles stored in a digital library and a single query will typically yield a large number of articles, among which only a small subset will indeed interest the user. To provide more effective and efficient information search, many systems are equipped with a recommendation subsystem that recommends articles that users might be interested. In this thesis, we aim to research a number of recommendation techniques for making personalized recommendation.
    In light of the previous work that used collaborative approach for making recommendation for literature digital libraries, in this thesis, we first propose three content-based recommendation approaches, followed by a set of hybrid approaches that combine both content-based and collaborative methods. These alternatives and approaches were evaluated using the web log of an operational electronic thesis system at NSYSU. It has been found the hybrid approaches yields better quality of articles recommendation.
    關鍵字(中)
  • 資訊擷取
  • 數位圖書館
  • 推薦系統
  • 個人化服務
  • 關鍵字(英)
  • Personalization
  • Information Retrieval
  • Recommendation System
  • Literature Digital library
  • 論文目次 CHAPTER 1 INTRODUCTION 1
    1.1 RESEARCH BACKGROUND 1
    1.2 RESEARCH MOTIVATIONS AND OBJECTIVES 1
    CHAPTER 2 LITERATURE REVIEW 4
    2.1 INFORMATION RETRIEVAL 4
    2.2 RECOMMENDER SYSTEMS 8
    2.2.1 Content-based filtering: 8
    2.2.2 Collaborative filtering: 9
    2.2.3 Web page recommender system 10
    2.3 DATA PREPARATION FOR WEB USAGE LOG 13
    2.4 MULTIPLE REFERENCE POINT SYSTEMS 15
    2.5 MULTILEVEL HYPERGRAPH PARTITION 17
    2.5.1 Coarsening phase 20
    2.5.2 Initial partitioning phase 21
    2.5.3 Uncoarseing and refinement phase 22
    CHAPTER 3 CONTENT-BASED AND HYBRID APPROACHES 23
    3.1 MULTIPLE REFERENCE POINTS APPROACH 24
    3.2 CLUSTERING BASED APPROACHES 25
    3.2.1 Feature partitioning 26
    3.2.2 Article partitioning approach 27
    3.3 HYBRID APPROACHES 28
    CHAPTER 4 EVALUATIONS 30
    4.1 PERFORMANCE METRICS 32
    4.2 EXPERIMENTAL RESULTS 34
    CHAPTER 5 CONCLUSIONS 42
    REFERENCES 43
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    口試委員
  • 魏志平 - 召集委員
  • 簡立峰 - 委員
  • 黃三益 - 指導教授
  • 口試日期 2003-07-10 繳交日期 2003-07-11

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