Identifying technology trend in patentdocuments with themes

• Main Authors: Kuo-yen Lu, 呂國彥
• Other Authors: Ping-Yu Hsu
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/66086265542374984398

碩士 === 國立中央大學 === 企業管理研究所 === 100 === Patent has recorded over 90% of the technique worldwide, patent has also been protected by the law in each country. However, as the technology completion has risen up nowadays, the business in each country has started the patent war, therefore, the analysis and implementation of patent has became more important in every business. Patent analysis is focusing on analyzing and combining the message from patent documentations. With statistics, data mining, and text mining, the message can be transformed into a huge role in decisions making and future predictions. Therefore, patent analysis has become a weapon for business to survive and protect their technology. In the past, the majority of the research in trend analysis uses statistics analysis to analyze the amount of keywords and patents. However, the keywords that could be found are limited in the technique that has been developed in years and no more new words could be found. And due to patent documents has the necessity to unveil the technique, the business uses substitute words or phrases to avoid the new words been found. Therefore, patent analysis can only find some obvious and important words but not the key words. This research use Chinese break words system to find the key word in patent documents, and based on Cross-Collection Mixture Model’s probability model to pick the words. This model uses the time sequences difference of the words, and uses the background model and common theme to delete frequent and indistinguishable word and common theme to collect the words the keep appearing under times. The patent documents can be quickly filtered and found the low appearing frequency and distinguishable words due to automation. Therefore, the searching and filter the popular but aged technology, and precisely detect the emerging technology from patent documents.