KEA: practical automatic keyphrase extraction
Proceedings of the fourth ACM conference on Digital libraries
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
Machine Learning
Training a naive bayes classifier via the EM algorithm with a class distribution constraint
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Boosting for transfer learning
Proceedings of the 24th international conference on Machine learning
Topic-bridged PLSA for cross-domain text classification
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Chinese Terminology Extraction Using Window-Based Contextual Information
CICLing '07 Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing
Improving the extraction of bilingual terminology from Wikipedia
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Chinese term extraction using minimal resources
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Domain adaptation with structural correspondence learning
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Transferring naive bayes classifiers for text classification
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
An approach for extracting bilingual terminology from Wikipedia
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
IEEE Transactions on Knowledge and Data Engineering
EM-based hybrid model for bilingual terminology extraction from comparable corpora
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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As an important part of information extraction, terminology extraction attracts more attention. Currently, statistical and rule-based methods are used to extract terminologies in a specific domain. However, cross-domain terminology extraction task has not been well addressed yet. In this paper we propose using EM-based transfer learning method for cross-domain Chinese terminology extraction. Firstly, a naive bayes model is learned from source domain. Then EM-based transfer learning algorithm is used to adapt the classifier learnt from source domain to target domain, which is in different data distribution and domain from source domain. The advantage of our proposed method is to enable the target domain to utilize the knowledge from the source domain. Experimental results between computer domain and environment domain show the proposed Chinese terminology extraction with EM-based transfer learning method outperforms traditional statistical terminology extraction method significantly.