Shahryar Baki
2017
ICE: Idiom and Collocation Extractor for Research and Education
Vasanthi Vuppuluri
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Shahryar Baki
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An Nguyen
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Rakesh Verma
Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics
Collocation and idiom extraction are well-known challenges with many potential applications in Natural Language Processing (NLP). Our experimental, open-source software system, called ICE, is a python package for flexibly extracting collocations and idioms, currently in English. It also has a competitive POS tagger that can be used alone or as part of collocation/idiom extraction. ICE is available free of cost for research and educational uses in two user-friendly formats. This paper gives an overview of ICE and its performance, and briefly describes the research underlying the extraction algorithms.
2016
University of Houston at CL-SciSumm 2016: SVMs with tree kernels and Sentence Similarity
Luis Moraes
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Shahryar Baki
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Rakesh Verma
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Daniel Lee
Proceedings of the Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL)
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