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The purpose of the Spam Filter Web Service is to assist colleges in making accurate and informed decisions on whether an application coming in through CCCApply is fraudulent or not. At the heart of the web service is a machine learning , continuous retraining model that does NOT make any decisions, it just predicts whether an application meets the specific "identifiers" that have been collected and analyzed by the model based on thousands of confirmed spam applications submitted by the colleges.
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The User Interface tool gives the colleges the ability to review each application
that has been identifiedflagged as fraud
, and through continuous learning allows the model to grow and learn based on the college's determinations.The articles below provide more details about the spam
and then make the final decision on whether they should be confirmed as fraud or not. The continuous learning and retraining of the model is based on the final confirmation by the college.
The links below provide an overview of the spam filter web service and
theuser interface
.:
- FAQ: Spam Filter Web Service
- Issue: Rise in Fraudulent Applications in CCCApply
- Ways We Are Addressing Fraud in CCCApply
- Machine Learning Research Study
- Spam Filter Web Service & User
- Machine Learning Model & Prediction Service
- Spam Filter User Interface
- College participation and best practices
- Ways to prevent fraud at your college
- Spam Filter Web Service YouTube Tutorial
| Note |
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Message to Colleges Even if your college is not having a problem with fraud today, there is 's a chance you may have a problem in the future. The spam filter web service will give you the tools and knowledge to address fraud now and in the future. |
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