近年來，由於科技的突破大大改變了人類的生活模式，網際網路的發達，全球化競爭加速，經濟全球化已成為一個顯著的趨勢，人力與知識在全球流動的速度愈來愈快，跨國組織與多國公司的影響力也隨之升高，就產業發展而言，單一技術已無法滿足需求，創新主要來自跨領域技術的整合。本研究將針對分析汽車產業中跨領域技術合作與跨國供應鏈關係，我們利用國際的汽車產業技術趨勢預測未來具有發展潛力的台灣汽車產業供應鏈公司，並加以扶植以強化產業的競爭力。
由於資訊科技的發達與進步，越來越多的財經資訊或新聞以電子化形式呈現，有許多的公司提供多樣的訊息，企業決策者可以利用新聞媒體資訊去輔助投資決策，本研究利用文字探勘技術來萃取出當前被熱烈討論的字詞視為新技術或新產品，且利用word2vec方法延伸這些被熱烈討論的新技術字詞，這些以word2vec方法找出的擴展詞皆為與新技術字詞語意相似的詞，另一方面，專利是最完備且公開的技術文件，每篇專利都代表著研發的產出，專利文件裡面清楚說明使用的方法與技術細節，因此，我們尋找出新技術趨勢後，利用技術趨勢找出專利佈局，我們以新技術或新產品的擴展詞作為關鍵詞，至美國專利資料庫搜尋專利文件內容中含有關鍵詞的專利，並且鎖定這些有在美國專利資料庫中申請專利的台灣公司，進而找出具有發展潛力的公司。
本研究以基於資料包絡分析法的麥氏生產力指數(DEA-based Malmquist productivity index)作為評估供應鏈公司企業績效之方法，實驗的結果顯示，以本研究所提出的方法找出的台灣供應鏈公司確實是具有發展潛力的。

In recent years, the breakthrough of science and technology has greatly changed human life. With the development of Internet and acceleration in global competition, economic globalization has become a major trend, and the influence of international organizations and multinational corporations are also becoming prominent. In terms of industrial development, single technologies can no longer meet the demand. Most innovations involve the technological integration across different domain. This study will focus on the analysis of technology collaboration across domain and international supply chain relation in automotive industry, to predict the promising Taiwanese automotive supply chain companies for the future.
With the development of information technology, enterprise decision makers can use news media to guide investment decisions. In this study, text mining is used to extract “hot” terms of new technologies and products from the news. These words are then used to find others potentially related to them, by using word2vec to search for words semantically similar as these new technologies and products, i.e. extended terms. On the other hand, patents are undoubtedly the most complete technical documents available to the public. Each patent represents the output of research and development. We thus use the extended terms of new technologies and products as keywords to search for patents with documents containing these keywords in the USPTO database, and identify these Taiwanese supply chain companies with patents in USPTO database.
This study adopts DEA-based Malmquist productivity index to evaluate the enterprise performance of supply chain companies. The experimental results show that the Taiwan companies identified with this method are indeed promising in their growth.

CHAPTER 1-Introduction ....................................................................................... 1
1.1. Background and Motivation............................................................................. 1
1.2. Results and Contribution................................................................................. 4
1.3. Overall Architecture......................................................................................... 4
CHAPTER 2-Literature Review............................................................................... 5
2.1. Text Mining ...................................................................................................... 5
2.2. Word2Vec ........................................................................................................ 8
2.3. Data Envelopment Analysis (DEA)................................................................. 10
CHAPTER 3-Methodology .................................................................................... 14
3.1. Research Process.......................................................................................... 14
3.2. Data Collection .............................................................................................. 16
3.3. Terms of Novel Technology Extraction .......................................................... 17
3.4. Keywords Analysis ........................................................................................ 20
3.5. Potential Business Discovery......................................................................... 22
CHAPTER 4-Experimental Results and Evaluation ............................................. 25
4.1. Dataset description........................................................................................ 25
4.2. Result on Terms of Novel Technology Extraction ......................................... 26
4.3. Result on Keywords Analysis........................................................................ 27
4.4. Result on Potential Business Discovery ....................................................... 29
4.5. Evaluation ..................................................................................................... 32
CHAPTER 5-Conclusion and Future work............................................................ 41
References ........................................................................................................... 42

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