Shahryar Baki


2017

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ICE: Idiom and Collocation Extractor for Research and Education
Vasanthi Vuppuluri | Shahryar Baki | An Nguyen | 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

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University of Houston at CL-SciSumm 2016: SVMs with tree kernels and Sentence Similarity
Luis Moraes | Shahryar Baki | Rakesh Verma | Daniel Lee
Proceedings of the Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL)