Abstract
In this paper, a resolution system is presented to tackle nominal and pronominal anaphora in biomedical literature by using rich set of syntactic and semantic features. Unlike previous researches, the verification of semantic association between anaphors and their antecedents is facilitated by exploiting more outer resources, including UMLS, WordNet, GENIA Corpus 3.02p and PubMed. Moreover, the resolution is implemented with a genetic algorithm on its feature selection. Experimental results on different biomedical corpora showed that such approach could achieve promising results on resolving the two common types of anaphora.
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Liang, T., Lin, YH. (2005). Anaphora Resolution for Biomedical Literature by Exploiting Multiple Resources. In: Dale, R., Wong, KF., Su, J., Kwong, O.Y. (eds) Natural Language Processing – IJCNLP 2005. IJCNLP 2005. Lecture Notes in Computer Science(), vol 3651. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11562214_65
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DOI: https://doi.org/10.1007/11562214_65
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