臺灣博碩士論文加值系統

專利的相關研究與討論一直都非常熱絡，公司在專利的申請數量上也是逐年升高，但多數的議題是針對專利佈局的決策處理對績效的影響，或是專利強度對企業績效的影響。而結合專利多樣性與專利強度來分析公司績效的相關研究卻鮮少人研究。本研究提出，以專利探勘技術從專利文件中提取特徵，計算的專利的多樣性及強度對財務績效的關聯與影響。公司的名單從德溫特公司發布的百大創新公司為主，並從美國專利與商標局與Google Patents獲取專利、Macrotrends網站獲取財務報表。將專利文本進行前處理後，使用TF-IDF技術提取專利特徵，並利用赫芬達爾指標與香濃多樣性指標計算題取出來的專利特徵的多樣化數據。使用前述所提到的特徵與財務報表中獲得的財務指標進行分析、建立模型。得到公司發表的專利與獲利之間是具有相關性，由此推斷財務績效與專利的緊密關係，能為未來提供探討企業專利佈局的方式及利用隱藏在專利中關鍵字預測企業發展趨勢之研究。

Patent-related research and discussions have always been very active. The number of patent applications by companies has increased yearly. However, many research topics is the impact of patenting strategy on performance or the impact of patent intensity on company performance. The goal of this study is to use patent mining to explore the impacts of patent diversity on enterprise finance performance. The selected companies are from the list of Derwent Top 100 Global Innovators 2020 by Clarivate Analytics, patents are from the United States Patent and Trademark Office (USPTO) and Google Patents, and the Financial Information is from the macrotrends website.
After pre-processing the patent text, we use TF-IDF to extract patent features and calculate the diversity data of patent characteristics by using Herfindahl-Hirschman Index (HHI) and Shannon's diversity index. Next, we analyze diversity data and financial indicators to build models. The patents are related to company profit, inferring the relationship between the company financial performance and patents. It can provide a way to explore the company's Patenting strategy, as well as using keywords hidden in patents to predict enterprise development trends.

摘要 I
Abstract III
謝誌 V
Table of Contents VI
List of Tables VIII
List of Figures IX
1. Introduction 1
2. Literature review 3
2.1 Patent 3
2.1.1 Patent value 5
2.1.2 Patent Mining 6
2.1.3 Patenting strategy 9
2.2 Diversity Index 11
2.2.1 Herfindahl-Hirschman Index (HHI) 11
2.2.2 Shannon Diversity Index 11
2.3 Corporate Innovation and Finance 12
2.4 Financial Index 13
2.4.1 Revenue 13
2.4.2 Operating cash flow (OCF) 14
2.4.3 Return on assets (ROA) 14
2.4.4 Non-operating income and expense 14
2.4.5 Income from continuous operations 15
2.4.6 Shares outstanding 15
2.4.7 Basic EPS 15
3. Methodology 17
3.1 Data collection 18
3.2 Feature extraction 19
3.2.1 Patent intensity index 20
3.2.2 Patent diversity index 23
3.3 Missing 25
3.4 Modeling 26
4. Experiments and results 27
4.1 Descriptive Statistics 27
4.2 Revenue 31
4.3 OCF 34
4.4 ROA 37
4.5 Non-operating income and expense 38
4.6 Income from continuous 40
4.7 Shares outstanding 42
4.8 Basic EPS 44
5. Conclusion 47
5.1 Research result 47
5.2 Research contribution 48
5.3 Research limitations 49
6. References 50
Appendix 1. The Correlation Matrix of Variables (model: Y) 53
Appendix 2. The Correlation Matrix of Variables (model: Y+1) 56
Appendix 3. The Correlation Matrix of Variables (model: Y+2) 60

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