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Machine Learning Legislation

There is a need among the advocacy and research communities to dissect bills quickly. These long and often mind-numbing documents are had to keep track of as changes come and go. This project will create tools to help in the analysis and access of government bills.

One primary use case is spending bills. This project will help create a database of spending; going through the text of spending bills to identify and organizing the what, where, how much, and who.

We will use two APIs provided by the Sunlight Foundation for this project to get access to machine readable versions of the bills.

Team

  • Matthew Heston
  • Madian Khabsa
  • Vrushank Vora
  • Ellery Wulczyn

License

Copyright (C) 2014 Data Science for Social Good Fellowship at the University of Chicago

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS," WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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Automatically identify earmarks in congressional spending bills

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