Business Event Curation: Merging Human and Automated Approaches

Authors

  • Yiqi Wang University of North Carolina at Chapel Hill
  • Huiying Ma University of North Carolina at Chapel Hill
  • Nichola Lowe University of North Carolina at Chapel Hill
  • Maryann Feldman University of North Carolina at Chapel Hill
  • Charles Schmitt University of North Carolina at Chapel Hill

DOI:

https://doi.org/10.1609/aaai.v30i1.9934

Keywords:

Information Extraction, Business Intelligence, Natural Language Processing, Curation

Abstract

We present preliminary work to construct a knowledge curation system to advance research in the study of regional economics. The proposed system exploits natural language processing (NLP) techniques to automatically implement business event extraction, provides a user-facing interface to assist human curators, and a feedback loop to improve the performance of the Information Extraction Model for the automated parts of the system. Progress to date has shown that we can improve standard NLP approaches for entity and relationship extraction through heuristic means and provide indexing of extracted relationships to aid curation.

AAAI 2016 Proceedings Cover

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Published

2016-03-05

How to Cite

Wang, Y., Ma, H., Lowe, N., Feldman, M., & Schmitt, C. (2016). Business Event Curation: Merging Human and Automated Approaches. Proceedings of the AAAI Conference on Artificial Intelligence, 30(1). https://doi.org/10.1609/aaai.v30i1.9934

Issue

Vol. 30 No. 1 (2016): Thirtieth AAAI Conference on Artificial Intelligence

Section

Student Abstracts and Posters