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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Guoyu Tang Yunqing Xia Cambria, E. Peng Jin |
| Copyright Year | 2013 |
| Description | Author affiliation: Temasek Labs., Nat. Univ. of Singapore, Singapore, Singapore (Cambria, E.) || Sch. of Comput. Sci., Leshan Normal Univ., Leshan, China (Peng Jin) || Dept. of Comput. Sci., Tsinghua Univ., Beijing, China (Guoyu Tang; Yunqing Xia) |
| 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. |
| Sponsorship | Leshan Normal Univ. |
| Starting Page | 409 |
| Ending Page | 414 |
| File Size | 198071 |
| Page Count | 6 |
| File Format | |
| e-ISBN | 9781479925490 |
| DOI | 10.1109/CIS.2013.93 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-12-14 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Context Adaptation models Dictionaries cross-lingual document clustering Semantics Clustering algorithms Educational institutions cross-lingual document representation Vectors Word sense |
| Content Type | Text |
| Resource Type | Article |
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