Abstract
Lots of valuable textual information is used to extract relations between named entities from literature. Composite kernel approach is proposed in this paper. The composite kernel approach calculates similarities based on the following information: (1) Phrase structure in convolution parse tree kernel that has shown encouraging results. (2) Predicate-argument structure patterns. In other words, the approach deals with syntactic structure as well as semantic structure using a reciprocal method. The proposed approach was evaluated using various types of test collections and it showed the better performance compared with those of previous approach using only information from syntactic structures. In addition, it showed the better performance than those of the state of the art approach.
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Chun, HW., Jeong, CH., Song, SK., Choi, YS., Choi, SP., Sung, WK. (2011). Relation Extraction Based on Composite Kernel Combining Pattern Similarity of Predicate-Argument Structure. In: Kim, Th., et al. U- and E-Service, Science and Technology. UNESST 2011. Communications in Computer and Information Science, vol 264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27210-3_35
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DOI: https://doi.org/10.1007/978-3-642-27210-3_35
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