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Enhancing Spam Detection with Distributed Content-Insensitive Features

This project explores a new approach to spam detection through Declarative Networking, introducing Distributed Content-Insensitive Spam Detection (D-CISD). By focusing on content-agnostic features, the system enables real-time classification of spam without needing to open emails. This method promises scalable deployment and significant reduction of junk mail while maintaining transparency and simplicity in specification. Rapid customization and optimization are central to its implementation, aimed at improving email user experience.

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Enhancing Spam Detection with Distributed Content-Insensitive Features

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  1. New Ideas • Content insensitive features for spam detection • Using declarative networking for ease of deployment and optimizations D-CISD: Distributed Content Insensitive Spam Detection Peter Alvaro, Ashima Atul, Akhil Dhar and Beth Trushkowsky • Impact • Ability to throw out junk mail without opening the envelope. • Real-time classification of spammers and scalable deployment • Declarative approach achieves simplicity and transparency of specification. • Rapid implementation, customization and optimization. Tentative Schedule Nov 14 Status report Oct 10 Oct 23 Dec 12 Sep 19 Project discussion Sep 25 Project proposal Dec 9 Evaluation Results Design and Architecture Project report Feature selection Inference algorithms

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