Incorporating context information for the extraction of terms
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Extracting nested collocations
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
A measure of term representativeness based on the number of co-occurring salient words
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Two-character Chinese word extraction based on hybrid of internal and contextual measures
SIGHAN '03 Proceedings of the second SIGHAN workshop on Chinese language processing - Volume 17
Domain-specific keyphrase extraction
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Chinese terminology extraction using EM-Based transfer learning method
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
Hi-index | 0.00 |
Terminology extraction is an important work for automatic update of domain specific knowledge. Contextual information helps to decide whether the extracted new terms are terminology or not. As extraction based on fixed patterns has very limited use to handle natural language text, we need both syntactical and semantic information in the context of a term to determine its termhood. In this paper, we investigate two window-based context word extraction methods taking into account of syntactic and semantic information. Based on the performance of each method individually, a hybrid method which combines both syntactical and semantic information is proposed. Experiments show that the hybrid method can achieve significant improvement.