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Title: Mention Detection and Classification in Bio-chemical Domain using Conditional Random Field
Authors: Ekbal, A.
Saha, S.
Ravi, K.
Issue Date: Jan-2013
Publisher: IEEE Xplore
Abstract: Finding mentions of chemical names in texts is of huge interest due to its importance in wide-spread application areas. The inherent complex structures of chemical names and the existence of several representations and nomenclatures (like SMILES, InChI, IUPAC) pose a big challenge to their automatic identification and classification. In this paper we present a supervised machine learning approach based on Conditional Random Fields (CRF) to find mentions of IUPAC and IUPAC-like names in scientific text. We identify and implement a very rich feature set for the task without using any domain specific knowledge and/or resources. Experiments are carried out on the benchmark MEDLINE datasets. Evaluation shows encouraging performance with the overall recall, precision and F-measure values of 90.96%, 91.52% and 91.23%, respectively. We also present the scope of comparison to the existing state-of-the-art system(s).
Appears in Collections:2012

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