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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 魏志平(Chih-Ping Wei) | |
| dc.contributor.author | Ting-Yi Wang | en |
| dc.contributor.author | 王婷儀 | zh_TW |
| dc.date.accessioned | 2021-06-07T17:53:28Z | - |
| dc.date.copyright | 2012-08-28 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-08-17 | |
| dc.identifier.citation | [1] Ahuja, G., Lampert, C.M., 2001. Entrepreneurship in the large corporation: A longitudinal study of how established firms create breakthrough inventions. Strategic Management Journal 22 (6-7), pp.521-543.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/15845 | - |
| dc.description.abstract | With the rapid advancement of technologies over the last two decades, IP (intellectual property), especially patents, represents the most valuable and essential assets to firms. When leveraging effectively, it can serve as a powerful strategic and competitive tool. Identifying the technological novelty of patents has such a profound effect on competition and firm survival since it can help managers and decision makers detect drastic technological changes in the concerning technological fields, thus allowing them to plan responses at an early stage. However, identifying the technological novelty of patents is knowledge-intensive, time-consuming, and costly. Therefore, we apply data mining techniques to build an automatic system to accomplish this task. Specifically, we propose a TRIZ-based approach to evaluate the technological novelty of patents. Then, we integrate this approach with those proposed in prior studies (i.e., citation-based and text-based approaches) to form a more comprehensive framework for automatically classifying patents into different degrees of novelty. We conduct several experiments using an expert assessment dataset to evaluate the effectiveness of our proposed system. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-07T17:53:28Z (GMT). No. of bitstreams: 1 ntu-101-R99725037-1.pdf: 1281508 bytes, checksum: 5566382d5440cca2fa5c4a7f6adb7ce0 (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | TABLE OF CONTENTS
Chapter 1 Introduction 1 1.1 Background 1 1.2 Research Motivation and Objectives 5 Chapter 2 Literature Review 8 2.1 Citation-Based Approach (Bibliography) 8 2.2 Text-Based Approach (Claim Originality Analysis) 13 Chapter 3 Prediction Model of Patent Novelty 18 3.1 Variables Involved in the Prediction Model 18 3.2 Design of the Patent Novelty Prediction Model 27 Chapter 4 Evaluation and Result 30 4.1 Data Collection 30 4.2 Cross Validation 36 4.3 Empirical Evaluation Results 37 4.4 Evaluation of Early Assessment of Patent Novelty 45 Chapter 5 Conclusion 49 5.1 Conclusion 49 5.2 Future Work and Research Directions 50 References 51 Appendix 55 | |
| dc.language.iso | en | |
| dc.subject | 萃思 | zh_TW |
| dc.subject | 專利新穎性 | zh_TW |
| dc.subject | 引文分析 | zh_TW |
| dc.subject | 專利分析 | zh_TW |
| dc.subject | 資料探勘 | zh_TW |
| dc.subject | 專利探勘 | zh_TW |
| dc.subject | TRIZ | en |
| dc.subject | patent analysis | en |
| dc.subject | citation analysis | en |
| dc.subject | patent novelty | en |
| dc.subject | patent mining | en |
| dc.subject | data mining | en |
| dc.title | 透過文字及引文分析預測評估專利新穎性 | zh_TW |
| dc.title | How Novel is A Patent: Assessing Patent Novelty through Text and Citation Analysis | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 楊傳智(Chuen-Chi Yang),楊錦生(Chin-Sheng Yang),李彥賢(Yen-Hsien Lee) | |
| dc.subject.keyword | 專利新穎性,萃思,引文分析,專利分析,資料探勘,專利探勘, | zh_TW |
| dc.subject.keyword | patent novelty,TRIZ,citation analysis,patent analysis,data mining,patent mining, | en |
| dc.relation.page | 59 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2012-08-18 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
| 顯示於系所單位： | 資訊管理學系 | |
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|---|---|---|---|
| ntu-101-1.pdf 未授權公開取用 | 1.25 MB | Adobe PDF |
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