@InProceedings{hu-chen-chen:2016:COLING,
  author    = {HU, Renfen  and  Chen, Jiayong  and  Chen, Kuang-hua},
  title     = {The Construction of a Chinese Collocational Knowledge Resource and Its Application for Second Language Acquisition},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {3254--3263},
  abstract  = {The appropriate use of collocations is a challenge for second language
	acquisition. However, high quality and easily accessible Chinese collocation
	resources are not available for both teachers and students. This paper presents
	the design and construction of a large scale resource of Chinese collocational
	knowledge, and a web-based application (OCCA, Online Chinese Collocation
	Assistant) which offers free and convenient collocation search service to end
	users. We define and classify collocations based on practical language
	acquisition needs and utilize a syntax based method to extract nine types of
	collocations. Totally 37 extraction rules are compiled with word, POS and
	dependency relation features, 1,750,000 collocations are extracted from a
	corpus for L2 learning and complementary Wikipedia data, and OCCA is
	implemented based on these extracted collocations. By comparing OCCA with two
	traditional collocation dictionaries, we find OCCA has higher entry coverage
	and collocation quantity, and our method achieves quite low error rate at less
	than 5%. We also discuss how to apply collocational knowledge to grammatical
	error detection and demonstrate comparable performance to the best results in
	2015 NLP-TEA CGED shared task. The preliminary experiment shows that the
	collocation knowledge is helpful in detecting all the four types of grammatical
	errors.},
  url       = {http://aclweb.org/anthology/C16-1307}
}