Abstract
Anaphora resolution is one of the key problems in natural language processing. In natural language, in order to make language concise and to reduce redundancy, often using different words to replace the words or sentence of the same meaning. However, it is difficult for a computer to understand these issues as a human. Some researcher proposed using decision trees to solve this problem, but decision trees may have problems with over-matching. In this paper, we provide a better way called adaptive forest which combine random forest and adaptive boosting to resolve this problem. Experiment result shows the effectiveness of our method in anaphora resolution.
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Zhao, Y., Liu, J., Yin, C. (2018). Chinese Anaphora Resolution Based on Adaptive Forest. In: Park, J., Loia, V., Yi, G., Sung, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2017 2017. Lecture Notes in Electrical Engineering, vol 474. Springer, Singapore. https://doi.org/10.1007/978-981-10-7605-3_79
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DOI: https://doi.org/10.1007/978-981-10-7605-3_79
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