Midas: integrating public financial data

Authors:
Sreeram Balakrishnan;Vivian Chu;Mauricio A. Hernández;Howard Ho;Rajasekar Krishnamurthy;Shi Xia Liu;Jan H. Pieper;Jeffrey S. Pierce;Lucian Popa;Christine M. Robson;Lei Shi;Ioana R. Stanoi;Edison L. Ting;Shivakumar Vaithyanathan;Huahai Yang
Affiliations:
IBM Silicon Valley Lab, San Jose, CA, USA;IBM Research - Almaden, San Jose, CA, USA;IBM Research - Almaden, San Jose, CA, USA;IBM Research - Almaden, San Jose, CA, USA;IBM Research - Almaden, San Jose, CA, USA;IBM Research - China, Beijing, China;IBM Research - Almaden, San Jose, CA, USA;IBM Research - Almaden, San Jose, CA, USA;IBM Research - Almaden, San Jose, CA, USA;IBM Research - Almaden, San Jose, CA, USA;IBM Research - China, Beijing, China;IBM Research - Almaden, San Jose, CA, USA;IBM Silicon Valley Lab, San Jose, CA, USA;IBM Research - Almaden, San Jose, CA, USA;IBM Research - Almaden, San Jose, CA, USA
Venue:
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Year:
2010

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Abstract

The primary goal of the Midas project is to build a system that enables easy and scalable integration of unstructured and semi-structured information present across multiple data sources. As a first step in this direction, we have built a system that extracts and integrates information from regulatory filings submitted to the U.S. Securities and Exchange Commission (SEC) and the Federal Deposit Insurance Corporation (FDIC). Midas creates a repository of entities, events, and relationships by extracting, conceptualizing, integrating, and aggregating data from unstructured and semi-structured documents. This repository enables applications to use the extracted and integrated data in a variety of ways including mashups with other public data and complex risk analysis.