Abstract
We describe one approach to build an automatically trainable anaphora resolution system. In this approach, we used Japanese newspaper articles tagged with discourse information as training examples for a machine learning algorithm which employs the C4.5 decision tree algorithm by Quinlan [10]. Then, we evaluate and compare the results of several variants of the machine learning-based approach with those of our existing anaphora resolution system which uses manually-designed knowledge sources. Finally, we will compare our algorithms with those in the related work.
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References
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© 1996 Springer-Verlag Berlin Heidelberg
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Aone, C., Bennett, S.W. (1996). Applying machine learning to anaphora resolution. In: Wermter, S., Riloff, E., Scheler, G. (eds) Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing. IJCAI 1995. Lecture Notes in Computer Science, vol 1040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60925-3_55
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DOI: https://doi.org/10.1007/3-540-60925-3_55
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