Term Set Expansion based on Multi-Context Term Embeddings: an End-to-end Workflow
Mamou, Jonathan, Pereg, Oren, Wasserblat, Moshe, Dagan, Ido, Goldberg, Yoav, Eirew, Alon, Green, Yael, Guskin, Shira, Izsak, Peter, Korat, Daniel
–arXiv.org Artificial Intelligence
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 (some images were blurred for privacy reasons).
arXiv.org Artificial Intelligence
Jul-26-2018
- Country:
- North America > United States > New York (0.29)
- Genre:
- Research Report (0.40)
- Workflow (0.62)
- Technology: