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Ontology-Based Computing of Sentence Similarity

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1075))

Abstract

Sentence similarity is the basis for many natural language processing tasks and it is studied in this paper by the tools of ontology and Wikipedia-based Wiktionary. If a word appears in the definition of another word in Wiktionary, the two words can be said to be related to each other. Based on this kind of knowledge from Wiktionary, a graph-based ontology is built. In the graph, nodes represent words, and if one word appears in the definition of the other, there is a line between them in the graph. And the line or degree as it is called is used to compute word similarity. Accordingly, word similarity is used to compute sentence similarity. In the paper, content words such as nouns, verbs, adjectives and adverbs are used to computer sentence similarity. Sentence similarity computed in this way is effective for natural language processing tasks such as question answering, information extraction, etc. And it is used in online chat robot “FreeTalker”.

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Correspondence to Zixian Zhang .

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Zhang, Z., Liu, X. (2020). Ontology-Based Computing of Sentence Similarity. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1075. Springer, Cham. https://doi.org/10.1007/978-3-030-32591-6_104

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