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.
|Title of host publication||COLING 2018 - 27th International Conference on Computational Linguistics, Proceedings of System Demonstrations|
|Publisher||Association for Computational Linguistics (ACL)|
|Number of pages||5|
|State||Published - 2018|
|Event||27th International Conference on Computational Linguistics, COLING 2018 - Santa Fe, United States|
Duration: 20 Aug 2018 → 26 Aug 2018
|Name||COLING 2018 - 27th International Conference on Computational Linguistics, Proceedings of System Demonstrations|
|Conference||27th International Conference on Computational Linguistics, COLING 2018|
|Period||20/08/18 → 26/08/18|
Bibliographical noteFunding Information:
This work was supported in part by an Intel ICRI-CI grant. The authors are grateful to Sapir Tsabari from Intel AI Lab for her help in the dataset preparation.
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