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Are you using the model to classify by topic, or show you stories that are similar to ones you’ve “liked” in the past?

• PaulHoule 4y ago
  Right now there is just one category being trained which is "will I like this?" but this is silly in many ways, particularly throwing arXiv papers and articles about sports and projects from GitHub into one big pot I will never be able to get my numbers up (like AUC) until I divide and conquer into better defined problems. The data structure I have in mind is something like a "tag" from flickr except that the tag can have a positive, negative or indeterminate (it wants to know what I think and might have a probability score) valence. Thus the tag could be "dog", "not a dog", "is this a dog?" all of which are different from no tag. There's the need to define some kind of ontology that schedules certain questions to be asked based on the answers to other questions but that's another step. In the interest of long-term scalability but some short-term pain I want a single system to be able to handle a few "projects" simultaneously, for instance I also like sorting and categorizing images and I might want to look at 5000 abstracts from PubMed that match a query and would like to do all this without making new instances of the system.