Cross-language and cross-encyclopedia article linking using mixed-language topic model and hypernym translation

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Abstract

Creating cross-language article links among different online encyclopedias is now an important task in the unification of multilingual knowledge bases. In this paper, we propose a cross-language article linking method using a mixed-language topic model and hypernym translation features based on an SVM model to link English Wikipedia and Chinese Baidu Baike, the most widely used Wiki-like encyclopedia in China. To evaluate our approach, we compile a data set from the top 500 Baidu Baike articles and their corresponding English Wiki articles. The evaluation results show that our approach achieves 80.95% in MRR and 87.46% in recall. Our method does not heavily depend on linguistic characteristics and can be easily extended to generate crosslanguage article links among different online encyclopedias in other languages. © 2014 Association for Computational Linguistics.

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Wang, Y. C., Wu, C. K., & Tsai, R. T. H. (2014). Cross-language and cross-encyclopedia article linking using mixed-language topic model and hypernym translation. In 52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Proceedings of the Conference (Vol. 2, pp. 586–591). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/p14-2096

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