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| Title: | 基於BERT分析專利訴訟風險之方法:以Apple Watch關聯訴訟為例
A Method for Analyzing Patent Litigation Risk Based on BERT: A Case Study of Litigations Related to Apple Watch |
| Authors: | 沈孟葳
Shen, Meng-Wei |
| Contributors: | 宋皇志
Sung, Huang-Chih
沈孟葳
Shen, Meng-Wei |
| Keywords: | 專利分析
專利訴訟風險分析
自然語言處理
智慧型穿戴裝置
BERT預訓練模型
Patent Analysis
Patent Litigation Risk Analysis
Natural Language Processing
Smart Wearable Devices
BERT Pre-trained Model |
| Date: | 2023 |
| Issue Date: | 2023-09-01 14:51:51 (UTC+8) |
| Abstract: | 專利訴訟的發生和結果，可能造成企業負擔高額訴訟費用、支出鉅額賠償金、產品遭政府禁售和產品喪失技術獨佔性等重大負面影響，因此專利訴訟風險的分析和預警，對於企業而言至關重要。
在大數據時代，智慧型手錶、運動手環等具備生理數據追蹤功能的智慧型穿戴裝置，是在健康保健和醫療領域中大數據的重要貢獻者，裝置數據流結合大數據分析技術，為醫療保健領域帶來的革命性機會，因此吸引越來越多的公司投入競爭及相關技術的開發中。由於市場層面的競爭和巨大的潛在商機，專利侵權訴訟也頻繁發生。
本研究旨在提出一種方法，使企業得以在更符合經濟效益的情形下，進行專利訴訟風險分析的工作。為此本研究基於深度學習模型BERT，提出能夠協助企業提前辨識出有較高可能性提出專利侵權訴訟之公司，以及篩選出有較高風險被用於提起訴訟之專利的方法。本研究並以關聯於智慧型穿戴裝置中的代表性產品Apple Watch的數宗法院或ITC專利侵權訴訟，以及PTAB複審案件，作為本研究個案，測試本研究分析方法的有效性。個案測試結果顯示，三家標的競爭公司皆排序於前0.5%，專利侵權訴訟中的15件涉訟專利有8件排序於前10%，25件複審案件中有20件至少有1件舉發用前案排序在前10%，顯示本研究提出的分析方法，可以幫助企業挑選出較有可能造成威脅的競爭公司及專利，同時聚焦公司產品或服務中較可能發生侵權風險的技術，協助專利訴訟風險分析工作的進程。
The occurrence and outcome of patent litigation may result in significant negative impacts on a business, such as bearing high litigation costs, paying substantial damages, facing governmental product bans, and losing product technical exclusivity. Therefore, the analysis and early warning of patent litigation risks are of paramount importance for businesses.
In the era of big data, smart wearable devices such as smartwatches and fitness bands that have physiological data tracking functions are significant contributors to big data in the healthcare and medical fields. The combination of device data flow and big data analysis techniques brings revolutionary opportunities to the healthcare sector, attracting an increasing number of companies to enter the competition and engage in related technology development. Due to market competition and huge potential business opportunities, patent infringement lawsuits occur frequently.
The aim of this study is to propose a method that allows businesses to conduct patent litigation risk analysis in a more cost-effective way. To this end, based on the deep learning model BERT, this study proposes a method that can help businesses identify in advance companies that are more likely to file patent infringement lawsuits, as well as screen for patents that are at higher risk of being used in litigation. This study further tests the effectiveness of this analytical method using several representative lawsuits related to the Apple Watch, a product associated with smart wearable devices, in court or the International Trade Commission (ITC) patent infringement litigation, as well as Patent Trial and Appeal Board (PTAB) review cases.
The case study results show that all three targeted competitor companies rank in the top 0.5%, eight out of fifteen patents involved in the patent infringement lawsuits rank in the top 10%, and in 25 review cases, 20 cases have at least one citation from previous cases ranking in the top 10%. These results indicate that the analysis method proposed in this study can help businesses identify competitors or patents that are more likely to pose a threat, and focus on technologies within the company`s products or services that are more likely to incur infringement risks, assisting the process of patent litigation risk analysis. |
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中文文獻
曾元顯 (2004)。 專利文字之知識探勘: 技術與挑戰。
鄭証元 (2021)。 專利訴訟風險的實證研究。 國立臺灣大學, Available from Airiti AiritiLibrary database. (2021年)。 |
| Description: | 碩士
國立政治大學
科技管理與智慧財產研究所
110364202 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0110364202 |
| Data Type: | thesis |
| Appears in Collections: | [科技管理與智慧財產研究所] 學位論文
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