@inproceedings{vuppuluri-etal-2017-ice,
title = "{ICE}: Idiom and Collocation Extractor for Research and Education",
author = "Vuppuluri, Vasanthi and
Baki, Shahryar and
Nguyen, An and
Verma, Rakesh",
editor = "Martins, Andr{\'e} and
Pe{\~n}as, Anselmo",
booktitle = "Proceedings of the Software Demonstrations of the 15th Conference of the {E}uropean Chapter of the Association for Computational Linguistics",
month = apr,
year = "2017",
address = "Valencia, Spain",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/E17-3027",
pages = "108--111",
abstract = "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.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="vuppuluri-etal-2017-ice">
<titleInfo>
<title>ICE: Idiom and Collocation Extractor for Research and Education</title>
</titleInfo>
<name type="personal">
<namePart type="given">Vasanthi</namePart>
<namePart type="family">Vuppuluri</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Shahryar</namePart>
<namePart type="family">Baki</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">An</namePart>
<namePart type="family">Nguyen</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Rakesh</namePart>
<namePart type="family">Verma</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2017-04</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics</title>
</titleInfo>
<name type="personal">
<namePart type="given">André</namePart>
<namePart type="family">Martins</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Anselmo</namePart>
<namePart type="family">Peñas</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Valencia, Spain</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>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.</abstract>
<identifier type="citekey">vuppuluri-etal-2017-ice</identifier>
<location>
<url>https://aclanthology.org/E17-3027</url>
</location>
<part>
<date>2017-04</date>
<extent unit="page">
<start>108</start>
<end>111</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T ICE: Idiom and Collocation Extractor for Research and Education
%A Vuppuluri, Vasanthi
%A Baki, Shahryar
%A Nguyen, An
%A Verma, Rakesh
%Y Martins, André
%Y Peñas, Anselmo
%S Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F vuppuluri-etal-2017-ice
%X 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.
%U https://aclanthology.org/E17-3027
%P 108-111
Markdown (Informal)
[ICE: Idiom and Collocation Extractor for Research and Education](https://aclanthology.org/E17-3027) (Vuppuluri et al., EACL 2017)
ACL
- Vasanthi Vuppuluri, Shahryar Baki, An Nguyen, and Rakesh Verma. 2017. 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, pages 108–111, Valencia, Spain. Association for Computational Linguistics.