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Extracting Structured Information via Automatic + Human Computation
Last modified: 2015-09-23
Abstract
We present a system for extracting structured information from unstructured text using a combination of information retrieval, natural language processing, machine learning, and crowdsourcing. We test our pipeline by building a structured database of gun violence incidents in the United States. The results of our pilot study demonstrate that the proposed methodology is a viable way of collecting large-scale, up-to-date data for public health, public policy, and social science research.
Keywords
natural language processing; crowdsourcing; gun violence
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