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.
Authors
Oren Pereg
Senior Deep Learning Data Scientist, Intel AI Lab, Artificial Intelligence Products Group
Peter Izsak
Deep Learning Data Scientist, Intel AI Lab, Artificial Intelligence Products Group
Ido Dagan
Yoav Goldberg
Yael Green
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