Abstract:
Semantic links within text play an important role in understanding text. Cause-effect link is one of the basic semantic links that represents logic order between represen...Show MoreMetadata
Abstract:
Semantic links within text play an important role in understanding text. Cause-effect link is one of the basic semantic links that represents logic order between representation components of text. The importance of cause-effect link has been recognized and investigated in linguistics, but it has not been accurately measured to support computing applications. This paper is to investigate the role of cause-effect link within scientific paper. Research is conducted along two paths: (1) Human observations: Professionals find cause-effect links within a set of given papers, and then observe the number, the distribution and the keywords coverage of cause-effect links within each paper. The statistical results show that cause-effect links cover 76% keywords within paper on average. (2) Automatically discover more cause-effect links within a set of papers by developing a pattern-based algorithm. The automatically discovered cause-effect links validate the properties drawn from human observations. Experiments show that the algorithm can extract more than 80% of manually labeled links, and the automatically extracted links contain 75% of keywords within paper on average.
Date of Conference: 15-17 August 2016
Date Added to IEEE Xplore: 16 January 2017
ISBN Information: