Automatic discovery of technology trends from patent text

Authors:
Youngho Kim;Yingshi Tian;Yoonjae Jeong;Ryu Jihee;Sung-Hyon Myaeng
Affiliations:
Information and Communications University, Yuseong-gu, Daejeon, South Korea;Information and Communications University, Yuseong-gu, Daejeon, South Korea;Information and Communications University, Yuseong-gu, Daejeon, South Korea;Information and Communications University, Yuseong-gu, Daejeon, South Korea;Information and Communications University, Yuseong-gu, Daejeon, South Korea
Venue:
Proceedings of the 2009 ACM symposium on Applied Computing
Year:
2009

Citing 10
Cited 3

Detecting emerging concepts in textual data mining

Computational information retrieval
Associative document retrieval by query subtopic analysis and its application to invalidity patent search

Proceedings of the thirteenth ACM international conference on Information and knowledge management
Using the patent co-citation approach to establish a new patent classification system

Information Processing and Management: an International Journal
Semantic language models for topic detection and tracking

NAACLstudent '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Proceedings of the HLT-NAACL 2003 student research workshop - Volume 3
Accurate unlexicalized parsing

ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Term distillation in patent retrieval

PATENT '03 Proceedings of the ACL-2003 workshop on Patent corpus processing - Volume 20
Can text analysis tell us something about technology progress?

PATENT '03 Proceedings of the ACL-2003 workshop on Patent corpus processing - Volume 20
Patent claim processing for readability: structure analysis and term explanation

PATENT '03 Proceedings of the ACL-2003 workshop on Patent corpus processing - Volume 20
A mixture model for contextual text mining

Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Visualization of patent analysis for emerging technology

Expert Systems with Applications: An International Journal

A framework for automatic TRIZ level of invention estimation of patents using natural language processing, knowledge-transfer and patent citation metrics

Computer-Aided Design
Query enhancement for patent prior-art-search based on keyterm dependency relations and semantic tags

IRFC'12 Proceedings of the 5th conference on Multidisciplinary Information Retrieval
Triple Helix innovation in China's dye-sensitized solar cell industry: hybrid methods with semantic TRIZ and technology roadmapping

Scientometrics

Quantified Score

Hi-index	0.00

Visualization

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.