Please use this identifier to cite or link to this item: https://doi.org/10.1109/CIS.2013.93
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dc.titleInducing word senses for cross-lingual document clustering
dc.contributor.authorTang, G.
dc.contributor.authorXia, Y.
dc.contributor.authorCambria, E.
dc.contributor.authorJin, P.
dc.date.accessioned2016-10-22T07:45:52Z
dc.date.available2016-10-22T07:45:52Z
dc.date.issued2013
dc.identifier.citationTang, 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
dc.identifier.isbn9781479925483
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/128923
dc.description.abstractCross-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.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/CIS.2013.93
dc.sourceScopus
dc.subjectCross-lingual document clustering
dc.subjectCross-lingual document representation
dc.subjectWord sense
dc.typeConference Paper
dc.contributor.departmentTEMASEK LABORATORIES
dc.description.doi10.1109/CIS.2013.93
dc.description.sourcetitleProceedings - 9th International Conference on Computational Intelligence and Security, CIS 2013
dc.description.page409-414
dc.identifier.isiut000351209000086
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