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    政大機構典藏 > 理學院 > 資訊科學系 > 學位論文 >  Item 140.119/94856
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/94856


    Title: 個人化廣告推薦軟體之設計與實做
    The Design and implementations of a personalized advertisement recommendation software
    Authors: 張宏嘉
    Chang, Hung Chia
    Contributors: 沈錳坤
    Shan, Man Kwan
    張宏嘉
    Chang, Hung Chia
    Keywords: 個人化
    廣告
    推薦系統
    Personalized
    Advertisement
    Recommendar System
    Date: 2007
    Issue Date: 2016-05-09 12:02:24 (UTC+8)
    Abstract: 鑑於國人網路依賴度越來越高,每人每日透過網路獲取豐富的資訊及資料,然而由於資訊過多也造成使用者不知道自己真正想要的資訊,因此找尋出個人化資訊勢必成為未來研究的方向。一般網路行銷廣告都是在分析使用者在網站上的行為,然而鮮少去分析到使用者端環境及儲存的資料。相較於使用者在網站上的行為,使用者端所留下的行為資訊更能夠反應出使用者的真正興趣,因此本研究主要探討在個人使用環境(如:PC、NB)中,透過使用者最常接觸的三種途徑(包括:上網瀏覽資訊、信件資訊及常用檔案內容資訊)來獲取使用者興趣的資訊,並且建構出一套個人化廣告推薦系統常駐於使用者端即時(real-time)記錄使用者的行為資訊。本系統運用推薦技術(Recommendation Technique)搭配關聯式法則(Association Rule)來將這些資訊有效的過濾並關聯出使用者的喜好及興趣,同時利用這些資訊上網找尋合適的廣告資料,用以建構出個人化廣告推薦模式。
    The rapid growth of Internet has changed the patterns of our life. Everyone can gain rich information on internet, but plenty of information will confuse user's ability to determine whether these information are useful. Therefore, the further trend is to discover personalized information. Many researches about internet marketing advertisement are mining user's behavior in website server, but scarce researches focus on client. Compared to user's behavior in website, the behavior information which stays in local environment (ex. PC, NB) can reflect user's profile more. Thus, this research mainly discuss how to record user's behavior information containing Web Page Title, E-mail Subject and Document Content in local environment and how to construct a personalized advertisement recommendation system resident in memory of local environment for timely (On-line) collecting user's behavior information to create “user profile” using recommendation technique and association rule. This system will utilize “user profile” to provide appropriate personalized advertisement for user. Finally, we apply several experiments to verify the feasibility of our system.
    第一章 導論............1
    1.1 研究背景..........1
    1.2 研究動機..........2
    1.3 研究問題與目的....2
    第二章 技術背景與相關研究.........4
    2.1 An Introduction to Recommendation........4
    2.2 Recommendation Approach...........5
    2.2.1 內容導向式(Content-based Filtering).........5
    2.2.2 協同過濾式 (Collaborative Filtering, CF)....8
    2.2.3 混合式 (Hybrid-based filtering).........9
    2.3 Extensions for Recommendation Techniques...10
    第三章 廣告推薦系統設計與架構........12
    3.1 系統元件及架構............12
    3.2 系統設計理念...........12
    3.2.1 資訊收集 (Data Collectotion).....13
    3.1.2 內容分析 (Content Analysis)......16
    3.1.3 使用者記錄 (User Profile)........23
    3.1.4 廣告推薦 (Ads Recommendation)....24
    第四章 系統實作............28
    4.1 系統實作相關技術背景.........28
    4.1.1 Microsoft Office Object Library.....28
    4.1.2 SHChangeNotifyRegister API.......30
    4.1.3 Socket Interface...........31
    4.1.4 POP3 Protocol.........32
    4.2 系統實作環境及方法介紹.......34
    4.2.1 .NET Framework........34
    4.2.2 Visual C# Developer.........35
    4.2.3 COM+元件服務.......36
    4.2.4 非同步控制機制.....36
    第五章 實驗與結果..........38
    5.1 收集使用者回應........38
    5.2 實驗設計及方法........39
    5.3 實驗結果及分析........41
    第六章 結論與未來研究方向..........45
    參考文獻..........46
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    Description: 碩士
    國立政治大學
    資訊科學學系
    94971008
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0094971008
    Data Type: thesis
    Appears in Collections:[資訊科學系] 學位論文

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