Lexical Resource For Medical Events: A Polarity Based Approach

2015 IEEE International Conference on Data Mining Workshop (ICDMW)(2015)

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摘要
The continuous sophistication in clinical information processing motivates the development of a dictionary like WordNet for Medical Events in order to convey the valuable information (e.g., event definition, sense based contextual description, polarity etc.) to the experts (e.g. medical practitioners) and non-experts (e.g. patients) in their respective fields. The present paper reports the enrichment of medical terms such as identifying and describing events, times and the relations between them in clinical text by employing three different lexical resources namely seed list of medical events collected from SemEval 2015 Task-6, the WordNet and an English medical dictionary. In particular, we develop WordNet for Medical Events (WME) that uses contextual information for word sense disambiguation of medical terms and reduce the communication gap between doctors and patients. We have proposed two approaches (Sequential and Combined) for identifying the proper sense of a medical event based on each of the three types of texts. The polarity lexicons e.g., SentiWordNet, Affect Word List and Taboda's adjective list have been used for implementing the polarity based Word Sense Disambiguation of the medical events from their glosses as extracted from the lexical resources. The proposed WME out-performed a previously proposed Lesk Word Sense Disambiguation in the range of 10-20%.
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关键词
Medical Event,WordNet,polarity,Word Sense Disambiguation
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