Context-Aware Machine Learning and Mobile Data Analytics: Automated Rule-Based Services with Intelligent Decision-Making
暫譯: 上下文感知機器學習與行動數據分析：具智慧決策的自動化規則基礎服務
Sarker, Iqbal, Colman, Alan, Han, Jun
- 出版商: Springer
- 出版日期: 2022-12-03
- 售價: $6,400
- 貴賓價: 9.5 折 $6,080
- 語言: 英文
- 頁數: 157
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3030885321
- ISBN-13: 9783030885328
-
相關分類:
Machine Learning、Data Science
海外代購書籍(需單獨結帳)
商品描述
Part I Preliminaries
1 Introduction to Context-Aware Machine Learning and Mobile Data
Analytics
1.1 Introduction
1.2 Context-Aware Machine Learning
1.3 Mobile Data Analytics
1.4 An Overview of this Book
1.5 Conclusion
References
2 Application Scenarios and Basic Structure for Context-Aware
Machine Learning Framework
2.1 Motivational Examples with Application Scenarios
2.2 Structure and Elements of Context-Aware Machine Learning
Framework
2.2.1 Contextual Data Acquisition
2.2.2 Context Discretization
2.2.3 Contextual Rule Discovery
2.2.4 Dynamic Updating and Management of Rules
2.3 Conclusion
References
3 A Literature Review on Context-Aware Machine Learning and
Mobile Data Analytics
3.1 Contextual Information
3.1.1 Definitions of Contexts
3.1.2 Understanding the Relevancy of Contexts
3.2 Context Discretization
3.2.1 Discretization of Time-Series Data
3.2.2 Static Segmentation
vii
viii Contents
3.2.3 Dynamic Segmentation
3.3 Rule Discovery
3.3.1 Association Rule Mining
3.3.2 Classification Rules
3.4 Incremental Learning and Updating
3.5 Identifying the Scope of Research
3.6 Conclusion
References
Part II Context-Aware Rule Learning and Management
4 Contextual Mobile Datasets, Pre-processing and Feature Selection
4.1 Smart Mobile Phone Data and Associated Contexts
4.1.1 Phone Call Log
4.1.2 Mobile SMS Log
4.1.3 Smartphone App Usage Log
4.1.4 Mobile Phone Notification Log
4.1.5 Web or Navigation Log
4.1.6 Game Log
4.1.7 Smartphone Life Log
4.1.8 Dataset Summary
4.2 Examples of Contextual Mobile Phone Data
4.2.1 Time-Series Mobile Phone Data
4.2.2 Mobile phone data with multi-dimensional contexts
4.2.3 Contextual Apps Usage Data
4.3 Data Preprocessing
4.3.1 Data Cleaning
4.3.2 Data Integration
4.3.3 Data Transformation
4.3.4 Data Reduction
4.4 Dimensionality Reduction
4.4.1 Feature Selection
4.4.2 Feature Extraction
4.4.3 Dimensionality Reduction Algorithms
4.5 Conclusion
References
5 Discretization of Time-Series Behavioral Data and Rule Generation
based on Temporal Context
5.1 Introduction
5.2 Requirements Analysis
5.3 Time-series Segmentation Approach
5.3.1 Approach Overview
5.3.2 Initial Time Slices Generation
5.3.3 Behavior-Oriented Segments Generation
Contents ix
5.3.4 Selection of Optimal Segmentation
5.3.5 Temporal Behavior Rule Generation using Time Segments
5.4 Effectiveness Comparison
5.5 Conclusion
References
6 Discovering User Behavioral Rules based on Multi-dimensional
Contexts
6.1 Introduction
6.2 Multi-dimensional Contexts in User Behavioral Rules
6.3 Requirements Analysis
6.4 Rule Mining Methodology
6.4.1 Identifying the Precedence of Context
6.4.2 Designing Association Generation Tree
6.4.3 Extracting Non-Redundant Behavioral Association Rules
6.5 Experimental Analysis
6.5.1 Effect on the Number of Produced Rules
6.5.2 Effect of Confidence Preference the Predicted Accuracy
6.5.3 Effectiveness Comparison
6.6 Conclusion
References
7 Recency-based Updating and Dynamic Management of Contextual
Rules
7.1 Introduction
7.2 Requirements Analysis
7.3 An Example of Recent Data
7.4 Identifying Optimal Period of Recent Log Data
7.4.1 Data Splitting...
商品描述(中文翻譯)
**第一部分 前言**
**1 引言：情境感知機器學習與行動數據分析**
1.1 引言
1.2 情境感知機器學習
1.3 行動數據分析
1.4 本書概述
1.5 結論
參考文獻
**2 情境感知機器學習框架的應用場景與基本結構**
2.1 應用場景的激勵範例
2.2 情境感知機器學習的結構與元素
2.2.1 情境數據獲取
2.2.2 情境離散化
2.2.3 情境規則發現
2.2.4 規則的動態更新與管理
2.3 結論
參考文獻
**3 情境感知機器學習與行動數據分析的文獻回顧**
3.1 情境資訊
3.1.1 情境的定義
3.1.2 理解情境的相關性
3.2 情境離散化
3.2.1 時間序列數據的離散化
3.2.2 靜態分段
3.2.3 動態分段
3.3 規則發現
3.3.1 關聯規則挖掘
3.3.2 分類規則
3.4 增量學習與更新
3.5 確定研究範圍
3.6 結論
參考文獻
**第二部分 情境感知規則學習與管理**
**4 情境行動數據集、預處理與特徵選擇**
4.1 智慧型手機數據與相關情境
4.1.1 通話記錄
4.1.2 簡訊記錄
4.1.3 智慧型手機應用程式使用記錄
4.1.4 手機通知記錄
4.1.5 網頁或導航記錄
4.1.6 遊戲記錄
4.1.7 智慧型手機生活記錄
4.1.8 數據集摘要
4.2 情境手機數據的範例
4.2.1 時間序列手機數據
4.2.2 具有多維情境的手機數據
4.2.3 情境應用程式使用數據
4.3 數據預處理
4.3.1 數據清理
4.3.2 數據整合
4.3.3 數據轉換
4.3.4 數據減少
4.4 維度減少
4.4.1 特徵選擇
4.4.2 特徵提取
4.4.3 維度減少演算法
4.5 結論
參考文獻
**5 基於時間情境的時間序列行為數據離散化與規則生成**
5.1 引言
5.2 需求分析
5.3 時間序列分段方法
5.3.1 方法概述
5.3.2 初始時間片生成
5.3.3 行為導向的片段生成
5.3.4 最佳分段的選擇
5.3.5 使用時間片生成時間行為規則
5.4 效能比較
5.5 結論
參考文獻
**6 基於多維情境的用戶行為規則發現**
6.1 引言
6.2 用戶行為規則中的多維情境
6.3 需求分析
6.4 規則挖掘方法論
6.4.1 確定情境的優先順序
6.4.2 設計關聯生成樹
6.4.3 提取非冗餘的行為關聯規則
6.5 實驗分析
6.5.1 對生成規則數量的影響
6.5.2 信心偏好對預測準確性的影響
6.5.3 效能比較
6.6 結論
參考文獻
**7 基於最近性更新與情境規則的動態管理**
7.1 引言
7.2 需求分析
7.3 最近數據的範例
7.4 確定最近日誌數據的最佳期間
7.4.1 數據分割...
作者簡介
Iqbal H. Sarker received his Ph.D. under the department of Computer Science and Software Engineering from Swinburne University of Technology, Melbourne, Australia in 2018. Currently, he is working as a faculty member of the Department of Computer Science and Engineering at Chittagong University of Engineering and Technology. He is one of the Research Founder of the International AIQT Foundation, Switzerland. His professional and research interests include - Data Science, Machine Learning, AI-Driven Computing, Cybersecurity Intelligence, Behavioral Analytics, Context-Aware Computing and IoT-Smart City Technologies. He has over 100 publications in leading venues including Journals (Journal of Network and Computer Applications - Elsevier, USA; Internet of Things - Elsevier; Expert Systems with Applications - Elsevier, UK; Journal of Big Data - Springer Nature, UK; Mobile Network and Applications - Springer, Netherlands; The Computer Journal, Oxford University Press, UK; IEEE Transactions on Artificial Intelligence, IEEE Access, USA and so on) and Conferences such as IEEE DSAA, IEEE Percom, ACM Ubicomp, ACM Mobiquitous, Springer LNCS PAKDD, Springer LNCS ADMA and so on. He is a member of IEEE and ACM.
Alan Colman: is an Adjunct Research Fellow in Software Engineering at Swinburne University of Technology, Melbourne. His main research focus is on adaptive service-oriented systems and architectures. He has also made research contributions to feature-oriented software engineering, context-aware computing, control-theoretic adaptation and performance prediction of software systems, and user-centric access control and data sharing with blockchain. He has over 150 publications in leading software journals and conference proceedings with over 2300 citations to his papers.
Jun Han: received his Ph.D. in Computer Science from the University of Queensland. Since 2003, he has been Professor of Software Engineering at Swinburne University of Technology. He has authored two books and published over 260 peer-reviewed articles in leading international journals and conferences. His current research interests include adaptive and context-aware systems, services and cloud systems engineering, software and service behavior mining, data-driven software engineering, software architectures, software security and performance
Paul Watters: Professor Paul A. Watters is Academic Dean at Academies Australasia Polytechnic, an ASX-listed higher education provider operating 18 colleges in Australia and Singapore. Professor Watters is also Honorary Professor of Security Studies and Criminology at Macquarie University, and Adjunct Professor of Cyber Security at La Trobe University. He has worked closely with many large companies and law enforcement agencies in Australia on applied cyber R&D projects, and he has written many books and academic papers on cybersecurity, cybercrime and related topics. His research has been cited 4,964 times, and his h-index is 33. He obtained his PhD at Macquarie University in 2000, and read for his MPhil at the University of Cambridge in 1997 after completing a BA(First Class Honours) at the University of Tasmania, and a BA at the University of Newcastle. Professor Watters is a Fellow of the British Computer Society, a Senior Member of the IEEE, a Chartered IT Professional, and a Member of the Australian Psychological Society.
作者簡介(中文翻譯)
Iqbal H. Sarker 於2018年在澳洲墨爾本的斯威本科技大學（Swinburne University of Technology）計算機科學與軟體工程系獲得博士學位。目前，他在吉大港工程與科技大學（Chittagong University of Engineering and Technology）的計算機科學與工程系擔任教職。他是瑞士國際AIQT基金會的研究創始人之一。他的專業和研究興趣包括：數據科學、機器學習、人工智慧驅動計算、網絡安全情報、行為分析、情境感知計算以及物聯網智慧城市技術。他在多個領先的期刊上發表了超過100篇論文，包括《網絡與計算機應用期刊》（Journal of Network and Computer Applications - Elsevier, USA）、《物聯網》（Internet of Things - Elsevier）、《應用專家系統》（Expert Systems with Applications - Elsevier, UK）、《大數據期刊》（Journal of Big Data - Springer Nature, UK）、《移動網絡與應用》（Mobile Network and Applications - Springer, Netherlands）、《計算機期刊》（The Computer Journal, Oxford University Press, UK）、《IEEE人工智慧期刊》（IEEE Transactions on Artificial Intelligence）、《IEEE Access, USA》等等，以及IEEE DSAA、IEEE Percom、ACM Ubicomp、ACM Mobiquitous、Springer LNCS PAKDD、Springer LNCS ADMA等會議。他是IEEE和ACM的成員。
Alan Colman: 是斯威本科技大學（Swinburne University of Technology）軟體工程的兼任研究員。他的主要研究重點是自適應服務導向系統和架構。他還在特徵導向軟體工程、情境感知計算、控制理論適應、軟體系統性能預測以及以用戶為中心的訪問控制和區塊鏈數據共享方面做出了研究貢獻。他在領先的軟體期刊和會議論文集中發表了超過150篇論文，並且他的論文被引用超過2300次。
Jun Han: 於昆士蘭大學獲得計算機科學博士學位。自2003年以來，他一直擔任斯威本科技大學的軟體工程教授。他著有兩本書，並在國際領先的期刊和會議上發表了超過260篇經過同行評審的文章。他目前的研究興趣包括自適應和情境感知系統、服務和雲系統工程、軟體和服務行為挖掘、數據驅動的軟體工程、軟體架構、軟體安全和性能。
Paul Watters: Paul A. Watters教授是澳大利亞學院（Academies Australasia Polytechnic）的學術院長，該機構是一家在澳大利亞和新加坡運營18所學院的ASX上市高等教育提供者。Watters教授同時也是麥考瑞大學（Macquarie University）安全研究和犯罪學的名譽教授，以及拉籌伯大學（La Trobe University）的網絡安全兼任教授。他與澳大利亞的許多大型公司和執法機構在應用網絡研發項目上密切合作，並撰寫了許多有關網絡安全、網絡犯罪及相關主題的書籍和學術論文。他的研究被引用4964次，h指數為33。他於2000年在麥考瑞大學獲得博士學位，並在1997年於劍橋大學獲得碩士學位，之前在塔斯馬尼亞大學獲得一級榮譽學士學位，並在新卡索大學獲得學士學位。Watters教授是英國計算機學會的會員、IEEE的高級會員、特許IT專業人士，以及澳大利亞心理學會的成員。
