科技的發展對產業及經濟的進步有著舉足輕重的地位，而科技研發往往產出大量的技術文件及數據資料。科技進步和傳播透過大量的文集，如國際期刊、專利文件、開放型知識文件庫及重要國際標準等技術文件，才得以讓技術擴散他人分享，並繼續尋求精進的方法。企業若想藉著創新的科技發展新產品必須運用科技探勘找尋新科技組件。主題生成模型是強大的自然語言處理 Natural Language Processing (NLP)工具，此模型能夠分析文集及其相關關鍵字詞分布。本論文發展的技術探勘方法，稱之為 Excessive Topic Generation (ETG)，作為主題分析及視覺化的預處理框架。本論文發展出的ETG傳承了Latent Dirichlet Allocation (LDA) 的主題生成模式且具有生成字詞之間距離關係的學習能力。本研究以工業4.0之工業沉浸式科技 Industry Immersive Technology (IIT) 的科技組件探勘為案例，以系統化 ETG、LDA等方法，探討 IIT之科技發展趨勢。本研究檢索出超過11,000份技術文檔做為工業4. 0科技探勘文件庫。本研究亦以 IIT專利之國際專利分類 International Patent Classification (IPC)及合作專利分類 Cooperation Patent Classification (CPC)自動分類對 ETG的結果進行驗證及比較。智慧科技探勘使用 ETG前處理將使得集體智慧運用於工程諮詢及商業智能得以實現。

Science and technology play a major role in advancing industry with significant effects on the world economy. An inevitable consequence of the technology-driven economy has led to an increase in technical document data. Technology components are now spread across a huge corpus of international publications, patents, open source repositories, blogs, and essential standards. Businesses wanting to adopt technology must conduct technology mining for key component integrations. This dissertation contributes to an advanced technology mining method named Excessive Topic Generation (ETG) as a preprocessing framework for topic term (referred to as key term) generation, visualization, and analysis. The presented ETG method inherits the topic generation characteristics from Latent Dirichlet Allocation (LDA) with a further capability to generate word distance relationships among key terms. The framework is applied to a study of the advanced manufacturing domain encapsulated through Industry 4.0. Industry 4.0 outline combines conventional manufacturing practices with increased technological outreach over a corpus of more than 11,000 technical documents across public databases. A systematic drill down for Industrial Immersive Technology (IIT) over 2,164 technical documents covering Virtual Reality (VR), Augmented Reality (AR), and Brain Machine Interface (BMI) concepts are demonstrated. A validation comparison of 741 global IIT patents against international invention indexation standards International Patent Classification (IPC) and the Cooperative Patent Classification (CPC) are conducted to validate the superior ETG results. Further, a conversational chatbot is integrated to distribute generated transformation. Intelligent technology mining using ETG enables collective intelligence for both engineering consultation and business intelligence.

中文摘要 I
ABSTRACT II
ACKNOWLEDGMENT III
TABLE OF CONTENTS IV
LIST OF FIGURES VII
LIST OF TABLES VIII
1. INTRODUCTION 1
1.1 Background and Motivation 1
1.2 Research Objectives 3
1.3 Research Procedure 4
1.4 Thesis Organization 4
2. LITERATURE REVIEW 6
2.1 Technology Mining Overview 6
2.1.1 Technology Mining State of the Art Analysis 8
2.1.2 Empirical Studies 11
2.1.3 Intelligent Mining Approaches 13
2.2 Summary and Discussions 17
3. RESEARCH METHODOLOGY 20
3.1 Intelligent Technology Mining Using ETG 23
3.1.1 ETG Algorithm 25
3.2 System Requirements and Deployment 26
4. INDUSTRY 4.0 APPLICATION STUDY 28
4.1 Cyber Physical Systems (CPS) 30
4.2 Internet of Things (IoT) 33
4.3 Artificial Intelligence (AI) 35
4.4 Cloud and Big Data 37
4.5 Immersive Technologies 39
4.5.1 Technology Specifications 41
4.5.2 Governing Standards 43
4.5.3 Open Source Development 45
4.5.4 SDK and API Outreach 46
4.5.5 Patent Landscape 47
4.5.6 Patent Data Text Mining 51
4.5.7 ETG Key Term Discovery 54
4.5.8 Agglomerative Clustering 56
4.5.9 Key Findings 62
5. VALIDATIONS 66
6. CONVERSATIONAL INTERFACE INTEGRATION 71
6.1 System Design 72
6.2 System Demonstration 74
7. THESIS STATEMENT 78
8. CONCLUSIONS AND FUTURE SCOPE 81
REFERENCES 83
APPENDIX 1 – TECHNOLOGY MINING TERM FREQUENCY ANALYSIS 96
APPENDIX 2 – PUBLICATIONS WITH HIGH CITATIONS 98
APPENDIX 3 – INDUSTRY 4.0 PUBLICATIONS WITH HIGH CITATIONS 99
APPENDIX 4 – CPPS LITERATURE ONTOLOGY 102
APPENDIX 5 – IIoT LITERATURE ONTOLOGY 103
APPENDIX 6 – IIT KEY WORD COLLECTION 104
APPENDIX 7 – IMMERSIVE TECHNOLOGY TOP ASSIGNEE PATENTS 105
APPENDIX 8 – IIT TECHNOLOGY FUNCTION MATRIX 108
APPENDIX 9 – ETG TOP 150 TOPIC TERMS AND COUNT OF PATENTS 109
APPENDIX 10 – IIT ETG ONTOLOGY 111
APPENDIX 11 – “AUGMENTED” KEY PATENTS 112
APPENDIX 12 – KEY IIT PUBLICATIONS 114
APPENDIX 13 – KEY IIT PATENTS 115
APPENDIX 14 – KEY IIT STANDARDS 116
APPENDIX 15 – KEY OPEN SOURCE REPOSITORIES 117
APPENDIX 16 – PUBLICATIONS WITH A MANUFACTURING FOCUS 118

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