Automatic discovery of technology trends from patent text

Patent text is a rich source to discover technological progresses, useful to understand the trend and forecast upcoming advances. For the importance in mind, several researchers have attempted textual-data mining from patent documents. However, previous mining methods are limited in terms of readability, domainexpertise, and adaptability. In this paper, we first formulate the task of technological trend discovery and propose a method for discovering such a trend. We complement a probabilistic approach by adopting linguistic clues and propose an unsupervised procedure to discover technological trends. Based on the experiment, our method is promising not only in its accuracy, 77% in R-precision, but also in its functionality and novelty of discovering meaningful technological trends. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval – Clustering H.4.m [Information Systems]: Information Systems Application – Miscellaneous G...

• Type: Conference
• Year: 2009
• Where: SAC
• Authors: Youngho Kim, Yingshi Tian, Yoonjae Jeong, Jihee Ryu, Sung-Hyon Myaeng
• Keywords: Applied Computing, Forecast Upcoming Advances, SAC 2009, Technological Trend Discovery, Technological Trends