Context-dependent metaphor interpretation based on semantic relatedness

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Abstract

The previous work of metaphor interpretation mostly focused on single-word verbal metaphors and ignored the influence of contextual information, leading to some limitations(e.g. ignore the polysemy of metaphor). In this paper, we creatively propose the aspect-based semantic relatedness, and we present a novel metaphor interpretation method based on semantic relatedness for context-dependent nominal metaphors. First, we obtain the possible comprehension aspects according to the properties of source domain. Then, combined with contextual information, we calculate the degree of relatedness between the target and source domains from different aspects. Finally, we select the aspect which makes the relatedness between target and source domains maximum as comprehension aspect, and the metaphor explanation is formed with corresponding property of source domain. The results show that our method has higher accuracy. In particular, when the information of target domain is insufficient in corpus, our method still exhibits the good performance.

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Su, C., Huang, S., & Chen, Y. (2015). Context-dependent metaphor interpretation based on semantic relatedness. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9362, pp. 182–193). Springer Verlag. https://doi.org/10.1007/978-3-319-25207-0_16

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