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ICE

Idiom, Collocation Extractor

Code and supplemental materials for the following studies:

  • Vuppuluri, Vasanthi, Shahryar Baki, An Nguyen, and Rakesh Verma. "ICE: Idiom and Collocation Extractor for Research and Education." In Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics, pp. 108-111. 2017. BibTeX
  • Verma, Rakesh, Vasanthi Vuppuluri, An Nguyen, Arjun Mukherjee, Ghita Mammar, Shahryar Baki, and Reed Armstrong. "Mining the Web for Collocations: IR Models of Term Associations." In International Conference on Intelligent Text Processing and Computational Linguistics, pp. 177-194. Springer, Cham, 2016. BibTeX
  • Verma, Rakesh, and Vasanthi Vuppuluri. "A new approach for idiom identification using meanings and the Web." In Proceedings of the International Conference Recent Advances in Natural Language Processing, pp. 681-687. 2015. BibTeX

How to run:

 - 'example_collocation.py' are 'example_idiom.py' are samples for running the code.
 - Bing API subscription key is required for running the sample code.
 - Subscription key can be obtained from 
   https://www.microsoft.com/cognitive-services/en-US/subscriptions for free (with limited number of queries)

License

The code and materials are made available without warranty for research, teaching ad scholarship purposes only, with further parameters in the spirit of a Creative Commons Attribution-NonCommercial License. You are free to use the provided resources as long as you attribute the authors by citing the orginal CICLING16, RANLP15 and EACL17 papers. For other uses or questions, please contact Prof. Rakesh Verma