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系統識別號 U0026-0812200910220339
論文名稱(中文) 行動網絡環境下之服務樣式探勘機制
論文名稱(英文) A Data Mining Mechanism for Discovering Service Patterns in Mobile Web Environments
校院名稱 成功大學
系所名稱(中) 資訊工程學系碩博士班
系所名稱(英) Institute of Computer Science and Information Engineering
學年度 90
學期 2
出版年 91
研究生(中文) 崔青福
研究生(英文) Ching-Fu Tsui
電子信箱 giles@dblab.csie.ncku.edu.tw
學號 p7689132
學位類別 碩士
語文別 中文
論文頁數 59頁
口試委員 口試委員-李建億
指導教授-曾新穆
口試委員-李強
口試委員-鄭憲宗
召集委員-吳宗憲
中文關鍵字 位置衍生式服務  多層級探勘  關聯規則  行動網絡  資料探勘 
英文關鍵字 Data Mining  Mobile Web Services  Association Rules Mining  Multi-Level Mining  Location-based Service 
學科別分類
中文摘要 本論文提出適用於行動網絡環境之資料探勘方法。雖然目前在行動通訊領域已經有一些相關的資料探勘研究,但是卻只侷限於其中某個部分,例如使用者的移動路徑探勘、使用者使用服務探勘。這些探勘研究並不能完整的表達出行動網絡環境中所隱含之資訊,使用者在某地點使用某服務之樣式。因此我們提出一個新的探勘方法,稱做二維多層級關聯規則探勘法,此方法考慮行動網絡之位置與服務皆具有多階層之特性,以多層級探勘概念套用於探勘程序中,讓找出之樣式具有層級特性。另外有本論文所提出之探勘法有一些變形方法,主要是在多維度或是較大的資料量部分降低探勘所需時間。經由實驗證明,我們的方法確實可以找出完整的樣式,且在效率上、正確度、資料量的可擴充性都表現的不錯。最後,提出應用於行動網絡之探勘系統,可結合我們所提出之探勘方法於其中,配合個人化的預測機制,達到個人化的服務,可主動或被動的將預測結果提供給使用者。

英文摘要 This thesis presents a new data mining approach that can efficiently discover services patterns in mobile web environments. Although some studies have been made on data mining in mobile systems, they were mostly focused on topics like moving path mining and service request log mining, and the issue of discovering user’s service request patterns associated with the locations have not been explored. Therefore, we propose a new data mining mechanism named two-dimensional multi-level association rules mining, which can efficiently discover these patterns by taking into account the multilevel and hierarchical characteristic of the location and service concept. Moreover, several variations of the proposed mining mechanism were developed to reduce the mining time under high dimensional or large dataset. Through experimental evaluations, our methods were shown to deliver excellent performance in terms of accuracy, completeness, execution efficiency and scalability. Finally, we also depict how the proposed mining mechanism can be applied to predict a mobile user’s service request behavior such as to provide personalized services.

論文目次 英文摘要…………………………………………………………………………I
中文摘要…………………………………………………………………………III
誌謝………………………………………………………………………………IV
目錄………………………………………………………………………………V
表目錄……………………………………………………………………………IX
圖目錄……………………………………………………………………………X
第一章  導論……………………………………………………………… 1
1.1 研究背景……………………………………………………………………1
1.2 研究動機……………………………………………………………………1
1.3 問題描述……………………………………………………………………2
1.4 研究方法……………………………………………………………………3
1.5 論文架構……………………………………………………………………4
第二章 文獻探討………………………………………………………………6
2.1 PCS網路架構……………………………………………………………… 6
2.2 位置追蹤……………………………………………………………………7
2.3 通話程序……………………………………………………………………8
2.4 加值服務……………………………………………………………………9
2.5 WAP及GPRS服務…………………………………………………………… 10
2.6 關聯規則探勘法……………………………………………………………11
2.6.1 關聯規則之定義…………………………………………………………12
2.6.2 關聯規則探勘法的目的…………………………………………………12
2.6.3 關聯規則探勘法說明……………………………………………………12
2.7 Apriori演算法…………………………………………………………… 13
2.7.1 Apriori演算法說明…………………………………………………… 14
2.7.2 Apriori-gen函式說明………………………………………………… 14
2.7.3 Apriori範例…………………………………………………………… 15
2.8 多階層概念…………………………………………………………………16
2.9 多層級關聯規則探勘法……………………………………………………17
2.9.1 演算法ML_T2L1………………………………………………………… 10
2.10 用戶移動樣式探勘……………………………………………………… 20
2.10.1 LM演算法……………………………………………………………… 20
2.10.2 Scal演算法…………………………………………………………… 22
2.11 相關研究總結…………………………………………………………… 24
第三章 二維多層級關聯規則探勘法…………………………………………25
3.1 二維多層級關聯規則探勘法………………………………………………25
3.1.1二維多層級關聯規則探勘法之定義…………………………………… 25
3.1.2二維多層級關聯規則探勘法之目的…………………………………… 26
3.2 二維多層級關聯規則探勘法之演算法……………………………………26
3.2.1 Merge函數……………………………………………………………… 29
3.3 範例…………………………………………………………………………30
3.4 二維多層級關聯規則探勘法之變形………………………………………32
3.5 總結…………………………………………………………………………33
第四章 系統架構………………………………………………………………34
4.1 系統架構……………………………………………………………………34
4.2 資料整合元件………………………………………………………………35
4.2.1移動路徑資料…………………………………………………………… 35
4.2.2服務記錄資料…………………………………………………………… 36
4.2.3整合資料………………………………………………………………… 37
4.3 資料探勘元件………………………………………………………………38
4.4 個人化行為預測元件………………………………………………………39
第五章 實驗分析………………………………………………………………41
5.1 虛擬資料產生器暨基本資料組設定………………………………………41
5.2 基本資料組之Min. Support制定暨實驗…………………………………43
5.3 實驗規劃……………………………………………………………………45
5.4 Network實驗……………………………………………………………… 46
5.4.1 Nodes實驗……………………………………………………………… 46
5.4.2 Network Concept Level實驗………………………………………… 46
5.5 Service實驗……………………………………………………………… 48
5.5.1 Service Number實驗……………………………………………………48
5.5.2 Service Concept Level實驗………………………………………… 49
5.6 User Behavior實驗……………………………………………………… 50
5.6.1 Request Service實驗………………………………………………… 50
5.6.2 User Alive Time Units實驗………………………………………… 52
5.6.3 User Number實驗……………………………………………………… 52
5.7 實驗總結……………………………………………………………………53
第六章 結論與未來研究方向…………………………………………………54
6.1 結論…………………………………………………………………………54
6.2 應用…………………………………………………………………………54
6.3 未來研究方向………………………………………………………………55
參考文獻…………………………………………………………………………56
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