Summary of the paper
| Title | CLTC: A Chinese-English Cross-lingual Topic Corpus |
|---|---|
| Authors | Yunqing Xia, Guoyu Tang, Peng Jin and Xia Yang |
| Abstract | Cross-lingual topic detection within text is a feasible solution to resolving the language barrier in accessing the information. This paper presents a Chinese-English cross-lingual topic corpus (CLTC), in which 90,000 Chinese articles and 90,000 English articles are organized within 150 topics. Compared with TDT corpora, CLTC has three advantages. First, CLTC is bigger in size. This makes it possible to evaluate the large-scale cross-lingual text clustering methods. Second, articles are evenly distributed within the topics. Thus it can be used to produce test datasets for different purposes. Third, CLTC can be used as a cross-lingual comparable corpus to develop methods for cross-lingual information access. A preliminary evaluation with CLTC corpus indicates that the corpus is effective in evaluating cross-lingual topic detection methods. |
| Topics | Corpus (creation, annotation, etc.), Information Extraction, Information Retrieval, Multilinguality |
Full paper  |
CLTC: A Chinese-English Cross-lingual Topic Corpus |
| Bibtex | @InProceedings{XIA12.389, author = {Yunqing Xia and Guoyu Tang and Peng Jin and Xia Yang}, title = {CLTC: A Chinese-English Cross-lingual Topic Corpus}, booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)}, year = {2012}, month = {may}, date = {23-25}, address = {Istanbul, Turkey}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-7-7}, language = {english} } |