Abstract
We present an application of kernel methods for extracting relation between an aspect of an entity and an opinion word from text. Two tree kernels based on the constituent tree and dependency tree were applied for aspect-opinion relation extraction. In addition, we developed a new kernel by combining these two tree kernels. We also proposed a new model for sentiment analysis on aspects. Our model can identify polarity of a given aspect based on the aspect-opinion relation extraction. It outperformed the model without relation extraction by 5.8% on accuracy and 4.6% on F-measure.
An erratum for this chapter can be found at http://dx.doi.org/10.1007/978-3-319-18117-2_51
An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-3-319-18117-2_51
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Nguyen, T.H., Shirai, K. (2015). Aspect-Based Sentiment Analysis Using Tree Kernel Based Relation Extraction. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2015. Lecture Notes in Computer Science(), vol 9042. Springer, Cham. https://doi.org/10.1007/978-3-319-18117-2_9
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DOI: https://doi.org/10.1007/978-3-319-18117-2_9
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