Progress in language processing technology for electronic rulemaking

Authors:
Stuart Shulman;Eduard Hovy;Jamie Callan;Stephen Zavestoski
Affiliations:
University of Pittsburgh, Pittsburgh, PA;USC-ISI, Marina del Rey, CA;Carnegie Mellon University, Pittsburgh, PA;University of San Francisco, San Francisco, CA
Venue:
dg.o '06 Proceedings of the 2006 international conference on Digital government research
Year:
2006

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Abstract

In this project, we are developing new text processing tools that help people perform advanced analysis of large collections of text commentary. This problem is increasingly faced by the U.S. federal government's regulation writers who formulate the rules and regulations that define the details of laws enacted by Congress. Our research focuses on text clustering, text searching, near-duplicate detection, opinion identification, stakeholder characterization, and extractive summarization, as well as the impact of such tools on the process of rulemaking itself. Versions of a Rule-Writer's Workbench are being built by researchers at ISI and CMU, made available for experimental use by our government partners at the DOT and EPA, and evaluated by researchers at the Library and Information Science and Sociology departments at the universities of Pittsburgh and San Francisco, respectively. This project started in October 2004 and is funded for 3 years under the NSF's Digital Government Program.