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Automatic Discovery of Technology Trends from Patent Text
| Citations: | 3 - 1 self |
BibTeX
@MISC{Kim_automaticdiscovery,
author = {Youngho Kim and Yingshi Tian and Yoonjae Jeong and Ryu Jihee and Sung-hyon Myaeng},
title = {Automatic Discovery of Technology Trends from Patent Text},
year = {}
}
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Abstract
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, domain-expertise, 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.
Keyphrases
patent text technology trend automatic discovery technological progress previous mining method probabilistic approach textual-data mining unsupervised procedure technological trend discovery linguistic clue patent document several researcher technological trend meaningful technological trend forecast upcoming advance rich source
