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paper: Automated Knowledge Extraction from the Federal Acquisition Regulations System

paper: Automated Knowledge Extraction from the Federal Acquisition Regulations System

Tim Finin, 8:56pm 28 November 2017

Automated Knowledge Extraction from the Federal Acquisition Regulations System (FARS)

Srishty Saha and Karuna Pande Joshi, Automated Knowledge Extraction from the Federal Acquisition Regulations System (FARS), 2nd International Workshop on Enterprise Big Data Semantic and Analytics Modeling, IEEE Big Data Conference, December 2017.

With increasing regulation of Big Data, it is becoming essential for organizations to ensure compliance with various data protection standards. The Federal Acquisition Regulations System (FARS) within the Code of Federal Regulations (CFR) includes facts and rules for individuals and organizations seeking to do business with the US Federal government. Parsing and gathering knowledge from such lengthy regulation documents is currently done manually and is time and human intensive.Hence, developing a cognitive assistant for automated analysis of such legal documents has become a necessity. We have developed semantically rich approach to automate the analysis of legal documents and have implemented a system to capture various facts and rules contributing towards building an ef?cient legal knowledge base that contains details of the relationships between various legal elements, semantically similar terminologies, deontic expressions and cross-referenced legal facts and rules. In this paper, we describe our framework along with the results of automating knowledge extraction from the FARS document (Title48, CFR). Our approach can be used by Big Data Users to automate knowledge extraction from Large Legal documents.


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