SetExpander: End-to-end Term Set Expansion Based on Multi-Context Term Embeddings

Jonathan Mamou; Oren Pereg; Moshe Wasserblat; Ido Dagan; Yoav Goldberg; Alon Eirew; Yael Green; Shira Guskin; Peter Izsak; Daniel Korat

SetExpander: End-to-end Term Set Expansion Based on Multi-Context Term Embeddings

Jonathan Mamou
, Oren Pereg
, Moshe Wasserblat
, Ido Dagan
, Yoav Goldberg
, Alon Eirew
, Yael Green
, Shira Guskin
, Peter Izsak
, Daniel Korat

Department of Computer Science and Artificial Intelligence

Bar-Ilan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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 for term set expansion. 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 for solving real-life use cases including integration in an automated recruitment system and an issues and defects resolution system. A video demo of SetExpander is available at https://drive.google.com/open?id=1e545bB87Autsch36DjnJHmq3HWfSd1Rv .

Original language	English GB
Title of host publication	Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
Place of Publication	Santa Fe, New Mexico
Pages	58-62
Number of pages	5
State	Published - 1 Aug 2018

Access to Document

https://aclanthology.org/C18-2013

Cite this

@inproceedings{64f8294a29b540edb6eb41409dd96b34,

title = "SetExpander: End-to-end Term Set Expansion Based on Multi-Context Term Embeddings",

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 for term set expansion. 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 for solving real-life use cases including integration in an automated recruitment system and an issues and defects resolution system. A video demo of SetExpander is available at https://drive.google.com/open?id=1e545bB87Autsch36DjnJHmq3HWfSd1Rv .",

author = "Jonathan Mamou and Oren Pereg and Moshe Wasserblat and Ido Dagan and Yoav Goldberg and Alon Eirew and Yael Green and Shira Guskin and Peter Izsak and Daniel Korat",

year = "2018",

month = aug,

day = "1",

language = "الإنجليزيّة",

pages = "58--62",

booktitle = "Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations",

}

Mamou, J, Pereg, O, Wasserblat, M, Dagan, I , Goldberg, Y, Eirew, A, Green, Y, Guskin, S, Izsak, P & Korat, D 2018, SetExpander: End-to-end Term Set Expansion Based on Multi-Context Term Embeddings. in Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations. Santa Fe, New Mexico, pp. 58-62. <https://aclanthology.org/C18-2013>

SetExpander: End-to-end Term Set Expansion Based on Multi-Context Term Embeddings. / Mamou, Jonathan; Pereg, Oren; Wasserblat, Moshe et al.
Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations. Santa Fe, New Mexico, 2018. p. 58-62.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - SetExpander: End-to-end Term Set Expansion Based on Multi-Context Term Embeddings

AU - Mamou, Jonathan

AU - Pereg, Oren

AU - Wasserblat, Moshe

AU - Dagan, Ido

AU - Goldberg, Yoav

AU - Eirew, Alon

AU - Green, Yael

AU - Guskin, Shira

AU - Izsak, Peter

AU - Korat, Daniel

PY - 2018/8/1

Y1 - 2018/8/1

N2 - 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 for term set expansion. 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 for solving real-life use cases including integration in an automated recruitment system and an issues and defects resolution system. A video demo of SetExpander is available at https://drive.google.com/open?id=1e545bB87Autsch36DjnJHmq3HWfSd1Rv .

AB - 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 for term set expansion. 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 for solving real-life use cases including integration in an automated recruitment system and an issues and defects resolution system. A video demo of SetExpander is available at https://drive.google.com/open?id=1e545bB87Autsch36DjnJHmq3HWfSd1Rv .

M3 - منشور من مؤتمر

SP - 58

EP - 62

BT - Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations

CY - Santa Fe, New Mexico

ER -

SetExpander: End-to-end Term Set Expansion Based on Multi-Context Term Embeddings

Abstract

Access to Document

Fingerprint

Cite this