Email Management: Unsuppervised Learning

The project problems are: [login to view URL]: This is to predict if email received require a reply. For example if you receive 2o emails today in the in box, how can we predict that 4 or 5 urgently require a reply while the rest did not necessarily need a reply. The 1st part of this work is theory ..What I mean by theory is that I wan an algorithm that is new and could solve this problem and the theory to back this algorithm up that your solution will work and even better than existing solutions. [login to view URL]: Providing a new method or ways to summarize email messages. 1st part is theory with algorithm and why it will work better. 3. Email Clustering: how we could group incoming emails messages into [login to view URL] folders. Could someone help with the theory and later with the code if necessary. NOTE: There is an attached doc that explains more. Thanks. ## Deliverables 1) Complete and fully-functional working program(s) in executable form as well as complete source code of all work done. 2) Deliverables must be in ready-to-run condition, as follows (depending on the nature of the deliverables): a) For web sites or other server-side deliverables intended to only ever exist in one place in the Buyer's environment--Deliverables must be installed by the Seller in ready-to-run condition in the Buyer's environment. b) For all others including desktop software or software the buyer intends to distribute: A software installation package that will install the software in ready-to-run condition on the platform(s) specified in this bid request. 3) All deliverables will be considered "work made for hire" under U.S. Copyright law. Buyer will receive exclusive and complete copyrights to all work purchased. (No GPL, GNU, 3rd party components, etc. unless all copyright ramifications are explained AND AGREED TO by the buyer on the site per the coder's Seller Legal Agreement). ## Platform All Platform