Patent Invalidity Search: A Learning to Rank Approach

碩士 === 國立臺灣大學 === 資訊管理學研究所 === 102 === Patents are important resources nowadays. The inventor(s) or the assignee(s) who owns a patent has the exclusive right to prevent or exclude others from making, using, selling, offering to sell or importing the invention. Besides, firms can also use their paten...

Full description

Bibliographic Details
Main Authors: Kuang-Sheng Yu, 余光昇
Other Authors: 魏志平
Format: Others
Language:en_US
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/32545163477432253381
Description
Summary:碩士 === 國立臺灣大學 === 資訊管理學研究所 === 102 === Patents are important resources nowadays. The inventor(s) or the assignee(s) who owns a patent has the exclusive right to prevent or exclude others from making, using, selling, offering to sell or importing the invention. Besides, firms can also use their patents to prevent their products from being infringed, license out their patents to gain royalty fees, or attack other firms via patent infringement lawsuits. As the number of patents granted increases annually, it is more likely that a firm will face patent infringement lawsuits. When a company is accused of patent infringement, to protect itself from this lawsuit, it is a common practice that the defendant files a patent invalidity lawsuit against the plaintiff. To achieve this goal, the defendant should conduct prior art search on the focal patent to find prior arts whose existence can invalid the focal patent. Thus, this study takes the learning to rank approach to design our patent invalidity search technique. Our empirical evaluation result shows that the effectiveness of our proposed technique and its enhanced version is satisfactory in supporting patent invalidity search.