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2010
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Hypothesis generation and ranking based on event similarities

11 years 8 months ago
Hypothesis generation and ranking based on event similarities
Accelerated by the technological advances in the domain, the size of the biomedical literature has been growing rapidly. As a result, it is not feasible for individual researchers to comprehend and synthesize all the information related to their interests. Therefore, it is conceivable to discover hidden knowledge, or hypotheses, by linking fragments of information independently described in the literature. In fact, such hypotheses have been reported in the literature mining community; some of which have even been corroborated by experiments. This paper mainly focuses on hypothesis ranking and investigates an approach to identifying reasonable ones based on semantic similarities between events which lead to respective hypotheses. Our assumption is that hypotheses generated from semantically similar events are more reasonable. The validity of our approach is demonstrated in comparison with those based on term frequencies, often adopted in the related work. Categories and Subject Descrip...
Taiki Miyanishi, Kazuhiro Seki, Kuniaki Uehara
Added 17 May 2010
Updated 17 May 2010
Type Conference
Year 2010
Where SAC
Authors Taiki Miyanishi, Kazuhiro Seki, Kuniaki Uehara
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