SL - FII: Syntactic and Lexical Constraints with Frequency based Iterative Improvement for Disease Mention Recognition in News Headlines
نویسندگان
چکیده
News headlines are a vital source of information for the masses. Identifying diseases that are being spread or discovered is important to take necessary steps for their prevention and cure. Our system uses a syntactic and lexical constraint-based approach which then goes through a frequency analysis phase to extract meaningful disease names. In the task of top-150 (unique) disease mention recognition on the 2015 news headlines dataset, our approach shows 40% gain in accuracy in comparison to other baseline approaches, illustrating the benefit of our approach.
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