On 13-04-17 6:56 AM, Avik Pal wrote:
Meanwhile It would be much appreciated if someone can direct me toan labeled dataset available on line.
Leaving aside entirely the question of whether we should (or will) support any project that requires learning on this scale, as a former anti-spam researcher, I can at least answer this question.
Unfortunately, the answer is largely "good luck with that" -- good labelled email data is surprisingly hard to come by, and that challenge is one of the reasons I stopped doing research in that area.
When I was doing anti-spam research, the only viable public classified ham/spam set was the SpamAssassin one. I don't believe it's been maintained with modern messages and at this point it may be useless.
Shortly after I left the field, people started using the Enron data set, which is pretty well classified by now, but again, is pretty long in the tooth.
Given that you're going to want to be classifying mailing list data, you may have to produce some synthetic data sets using information from publicly available mailing lists (e.g. the public archives of mailman-developers are available) and combining them with other data sources (e.g. publicly available collections of spam). This won't have a whole lot of interesting sub-labels (some lists will have more than others, depending on their use of dlists/topics/pre-classification by the sender) and a synthetic set is generally regarded as a poor information source for reproducible results, but it could be enough in a pinch given that you're adding a feature rather than publishing scientific work.
Note that the GSoC timeline doesn't allow time for finding and creating such a set, so if you're going to use one, you should determine in advance what you'll be using and and be able to provide a link to the completely-ready-for-gsoc set in your proposal.
Terri