Term mining for relation visualization and exploration: The case of agricultural news reports in Taiwan

Yuen-Hsien Tseng, Yi Yang Lee, Te Yi Chan

研究成果: 會議貢獻類型同行評審

摘要

An efficient term mining method to build a general term network is presented for term relation visualization and exploration. Terms from each document in the corpus are first identified. They are subject to an analysis for their association weights, which are accumulated over all the documents. The resulting term association matrix is used to build a general term network. A set of terms having similar attributes can then be given to extract the desired sub-network from the general term network for visualization. This analysis scenario based on the collective terms of the same type enables evidence-based relation exploration. Our application examples show that term relations, be it causality, coupling, or others, can be effectively revealed and verified by the underlying corpus. This work contributes by presenting an efficient and effective term-relationship mining method and extending the applicability of term networks to a broader range of informetric tasks.

原文英語
頁面189-193
頁數5
出版狀態已發佈 - 2009
事件12th International Conference on Scientometrics and Informetrics, ISSI 2009 - Rio de Janeiro, 巴西
持續時間: 2009 七月 142009 七月 17

其他

其他12th International Conference on Scientometrics and Informetrics, ISSI 2009
國家巴西
城市Rio de Janeiro
期間2009/07/142009/07/17

ASJC Scopus subject areas

  • Information Systems

指紋 深入研究「Term mining for relation visualization and exploration: The case of agricultural news reports in Taiwan」主題。共同形成了獨特的指紋。

引用此