An Unsupervised Method for Entity Mentions Extraction in Chinese Text
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-49178-3_25
Reference11 articles.
1. Ittycheriah, A., Lita, L., Kambhatla, N., et al.: Identifying and tracking entity mentions in a maximum entropy framework. In: Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Companion Volume of the Proceedings of HLT-NAACL 2003–Short Papers-Volume 2, pp. 40–42. Association for Computational Linguistics (2003)
2. Li, W., Qian, D., Lu, Q., et al.: Detecting, categorizing and clustering entity mentions in Chinese text. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 647–654. ACM (2007)
3. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);J Chen,2005
4. Hacioglu, K., Douglas, B., Chen, Y.: Detection of entity mentions occurring in English and Chinese text. In: Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, pp. 379–386. Association for Computational Linguistics (2005)
5. Daumé III, H., Marcu, D.: A large-scale exploration of effective global features for a joint entity detection and tracking model. In: Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, pp. 97–104. Association for Computational Linguistics (2005)
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