Abstract
Wikipedia has been the largest knowledge repository on the Web. However, most of the semantic knowledge in Wikipedia is documented in natural language, which is mostly only human readable and incomprehensible for computer processing. To establish the missing link from Wikipedia to semantic network, this paper proposes a relation discovery method, which can: (1) discover and characterize a large collection of relations from Wikipedia by exploiting the relation pattern regularity, the relation distribution regularity and the relation instance redundancy; and (2) annotate the hyperlinks between Wikipedia articles with the discovered semantic relations. Finally we discover 14,299 relations, 105,661 relation patterns and 5,214,175 relation instances from Wikipedia, and this will be a valuable resource for many NLP and AI tasks.
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Han, X., Song, X., Sun, L. (2016). Large Scale Semantic Relation Discovery: Toward Establishing the Missing Link Between Wikipedia and Semantic Network. In: Chen, H., Ji, H., Sun, L., Wang, H., Qian, T., Ruan, T. (eds) Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data. CCKS 2016. Communications in Computer and Information Science, vol 650. Springer, Singapore. https://doi.org/10.1007/978-981-10-3168-7_6
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DOI: https://doi.org/10.1007/978-981-10-3168-7_6
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