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|Title:||Inducing word senses for cross-lingual document clustering||Authors:||Tang, G.
|Keywords:||Cross-lingual document clustering
Cross-lingual document representation
|Issue Date:||2013||Citation:||Tang, G., Xia, Y., Cambria, E., Jin, P. (2013). Inducing word senses for cross-lingual document clustering. Proceedings - 9th International Conference on Computational Intelligence and Security, CIS 2013 : 409-414. ScholarBank@NUS Repository. https://doi.org/10.1109/CIS.2013.93||Abstract:||Cross-lingual document clustering is the task of automatically organizing a large collection of cross-lingual documents into a few groups according to their content or topic. It is well known that language barrier and translation ambiguity are two challenging issues for cross-lingual document representation. To address such issues, we propose to represent cross-lingual documents through statistical word senses, which are learned from a parallel corpus by means of a novel cross-lingual word sense induction model. Furthermore, a sense clustering method is adopted to discover semantic relation of word senses, which are used to represent cross-lingual documents through a sense-based vector space model. Evaluation on a benchmarking dataset shows that the proposed model outperforms two state-of-the-art models in cross-lingual document clustering. © 2013 IEEE.||Source Title:||Proceedings - 9th International Conference on Computational Intelligence and Security, CIS 2013||URI:||http://scholarbank.nus.edu.sg/handle/10635/128923||ISBN:||9781479925483||DOI:||10.1109/CIS.2013.93|
|Appears in Collections:||Staff Publications|
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