On publishing Chinese linked open schema

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Abstract

Linking Open Data (LOD) is the largest community effort for semantic data publishing which converts the Web from a Web of document to a Web of interlinked knowledge. While the state of the art LOD contains billion of triples describing millions of entities, it has only a limited number of schema information and is lack of schema-level axioms. To close the gap between the lightweight LOD and the expressive ontologies, we contribute to the complementary part of the LOD, that is, Linking Open Schema (LOS). In this paper, we introduce Zhishi.schema, the first effort to publish Chinese linked open schema. We collect navigational categories as well as dynamic tags from more than 50 various most popular social Web sites in China. We then propose a two-stage method to capture equivalence, subsumption and relate relationships between the collected categories and tags, which results in an integrated concept taxonomy and a large semantic network. Experimental results show the high quality of Zhishi.schema. Compared with category systems of DBpedia, Yago, BabelNet, and Freebase, Zhishi.schema has wide coverage of categories and contains the largest number of subsumptions between categories. When substituting Zhishi.schema for the original category system of Zhishi.me, we not only filter out incorrect category subsumptions but also add more finer-grained categories.

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Wang, H., Wu, T., Qi, G., & Ruan, T. (2014). On publishing Chinese linked open schema. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8796, pp. 293–308). Springer Verlag. https://doi.org/10.1007/978-3-319-11964-9

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