Semantic search with domain-specific word-embedding and production monitoring in Fintech

Mojtaba Farmanbar; Nikki Van Ommeren; Boyang Zhao

COLING 2020system demonstrations3 citations

Semantic search with domain-specific word-embedding and production monitoring in Fintech

Mojtaba Farmanbar, Nikki Van Ommeren, Boyang Zhao

Abstract

We present an end-to-end information retrieval system with domain-specific custom language models for accurate search terms expansion. The text mining pipeline tackles several challenges faced in an industry-setting, including multi-lingual jargon-rich unstructured text and privacy compliance. Combined with a novel statistical approach for word embedding evaluations, the models can be monitored in a production setting. Our approach is used in the real world in risk management in the financial sector and has wide applicability to other domains.

BibTeX

@inproceedings{farmanbar-etal-2020-semantic,
    title = "Semantic search with domain-specific word-embedding and production monitoring in Fintech",
    author = "Farmanbar, Mojtaba  and
      Van Ommeren, Nikki  and
      Zhao, Boyang",
    editor = "Ptaszynski, Michal  and
      Ziolko, Bartosz",
    booktitle = "Proceedings of the 28th International Conference on Computational Linguistics: System Demonstrations",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "International Committee on Computational Linguistics (ICCL)",
    url = "https://aclanthology.org/2020.coling-demos.6/",
    doi = "10.18653/v1/2020.coling-demos.6",
    pages = "28--33"
}