A PERSONAL INFORMATION PUSH DELIVERY SYSTEM BASED ON KNOWLEDGE
戴偉勝、陳振東
E-mail: 9020016@mail.dyu.edu.tw
ABSTRACT
INTERNET PROVIDES A POWERFUL DISSEMINATIVE ABILITY FOR USERS TO ACQUIRE INFORMATION MORE EFFICIENT AND FAST. WHEREAS, INCREASING LARGE SCALE OF DATA INDUCED SOME PROBLEMS WHILE USERS FACE THE INFORMATION OVERLOAD SITUATION BECOME MORE SERIOUS. BY USING INFORMATION RETRIEVAL TECHNIQUE, INFORMATION PUSH DELIVERY PROVIDES A GOOD SOLUTION FOR USERS TO ACQUIRE RICH INFORMATION FROM INTERNET. IN FACT, PROVIDING THE PERSONAL SERVICE FOR USERS IS ONE OF THE MOST IMPORTANT ISSUES IN ELECTRONIC COMMERCE (EC)
ENVIRONMENT. IN ORDER TO INCREASE THE INTERACTION BETWEEN ENTERPRISES AND CUSTOMERS, MANY ENTERPRISES PROVIDE PERSONAL SERVICES TO IMPROVE MANAGEMENT PERFORMANCE AND COMPETITIVENESS. IN THIS STUDY, THE FUZZY RETRIEVAL AND SIMILARITY MEASUREMENT
TECHNIQUES ARE APPLIED TO ESTABLISH A PERSONAL INFORMATION PUSH DELIVERY SYSTEM. THIS SYSTEM WILL PROVIDE USERS FOR THE RIGHT AND INTERESTED INFORMATION EFFECTIVELY. FINALLY, ENTERPRISES CAN USE THE PERSONAL INFORMATION PUSH DELIVERY SYSTEM TO SATISFY DIFFERENT REQUIREMENTS FOR DIFFERENT USERS AND IMPROVE THE CUSTOMER SERVICE LEVEL.
Keywords : INFORMATION PUSH DELIVERY, INFORMATION RETRIEVAL, PERSONAL SERVICES, SIMILARITY MEASUREMENT.
Table of Contents
第一章 緒論--P1 第一節 研究背景--P1 一、 網際網路的興盛--P1 二、 網路工具的發展--P1 三、 個人化服務--P3 第二節 研究 動機--P4 第三節 研究目的--P5 一、 資訊分類--P5 二、 資訊推薦與評估--P5 三、 電子商務應用--P5 第四節 研究範圍--P6 第 五節 研究流程--P6 第二章 文獻探討--P8 第一節 推薦代理器--P8 一、 代理器特性--P8 二、 推薦代理器的類型--P10 三、 推 薦代理器系統架構--P12 第二節 模糊資訊擷取--P15 一、 萃取專有名詞--P16 二、 調整專有名詞權重--P17 第三節 相似度衡 量方法與比較--P19 一、 相似度衡量方法--P19 二、 相似度衡量方法的比較分析--P22 第四節 分類知識庫--P33 一、 知識 庫--P33 二、 知識取得--P35 三、 知識彙總--P35 四、 知識表達--P37 第三章 資訊推薦系統架構--P39 第一節 專有名詞權重 的調整方式--P39 第二節 調整後的相似度衡量方法--P40 第三節 個人化資訊推薦系統--P41 第四節 滿意度評估方法--P43 第 四章 系統設計與實證分析--P45 第一節 系統開發環境與工具--P45 第二節 系統架構說明--P45 一、 資訊推薦網站--P45 二、
資訊推薦主系統--P46 第三節 實驗流程與結果--P51 第四節 問題探討--P66 一、 資料樣本內容過短--P66 二、 網頁樣本以財 經方面較多--P67 三、 專有名詞向量個數的取捨--P67 第五章 結論與建議--P68 第一節 結論--P68 第二節 後續研究建議--P69 一、 分類知識庫的自我學習--P69 二、 使用者偏好調整--P70 三、 中文的斷詞--P70 參考文獻--P71
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