@inproceedings{mamou-etal-2018-term,
title = "Term Set Expansion based {NLP} Architect by {I}ntel {AI} Lab",
author = "Mamou, Jonathan and
Pereg, Oren and
Wasserblat, Moshe and
Eirew, Alon and
Green, Yael and
Guskin, Shira and
Izsak, Peter and
Korat, Daniel",
editor = "Blanco, Eduardo and
Lu, Wei",
booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
month = nov,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D18-2004",
doi = "10.18653/v1/D18-2004",
pages = "19--24",
abstract = "We present SetExpander, a corpus-based system for expanding a seed set of terms into a more complete set of terms that belong to the same semantic class. SetExpander implements an iterative end-to-end workflow. It enables users to easily select a seed set of terms, expand it, view the expanded set, validate it, re-expand the validated set and store it, thus simplifying the extraction of domain-specific fine-grained semantic classes. SetExpander has been used successfully in real-life use cases including integration into an automated recruitment system and an issues and defects resolution system.",
}
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<abstract>We present SetExpander, a corpus-based system for expanding a seed set of terms into a more complete set of terms that belong to the same semantic class. SetExpander implements an iterative end-to-end workflow. It enables users to easily select a seed set of terms, expand it, view the expanded set, validate it, re-expand the validated set and store it, thus simplifying the extraction of domain-specific fine-grained semantic classes. SetExpander has been used successfully in real-life use cases including integration into an automated recruitment system and an issues and defects resolution system.</abstract>
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%0 Conference Proceedings
%T Term Set Expansion based NLP Architect by Intel AI Lab
%A Mamou, Jonathan
%A Pereg, Oren
%A Wasserblat, Moshe
%A Eirew, Alon
%A Green, Yael
%A Guskin, Shira
%A Izsak, Peter
%A Korat, Daniel
%Y Blanco, Eduardo
%Y Lu, Wei
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2018
%8 November
%I Association for Computational Linguistics
%C Brussels, Belgium
%F mamou-etal-2018-term
%X We present SetExpander, a corpus-based system for expanding a seed set of terms into a more complete set of terms that belong to the same semantic class. SetExpander implements an iterative end-to-end workflow. It enables users to easily select a seed set of terms, expand it, view the expanded set, validate it, re-expand the validated set and store it, thus simplifying the extraction of domain-specific fine-grained semantic classes. SetExpander has been used successfully in real-life use cases including integration into an automated recruitment system and an issues and defects resolution system.
%R 10.18653/v1/D18-2004
%U https://aclanthology.org/D18-2004
%U https://doi.org/10.18653/v1/D18-2004
%P 19-24
Markdown (Informal)
[Term Set Expansion based NLP Architect by Intel AI Lab](https://aclanthology.org/D18-2004) (Mamou et al., EMNLP 2018)
ACL
- Jonathan Mamou, Oren Pereg, Moshe Wasserblat, Alon Eirew, Yael Green, Shira Guskin, Peter Izsak, and Daniel Korat. 2018. Term Set Expansion based NLP Architect by Intel AI Lab. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 19–24, Brussels, Belgium. Association for Computational Linguistics.