Extracting knowledge from knowledge graphs using Facebook Pytorch BigGraph.


Machine learning gives us the ability to train a model, which can convert data rows into labels in such a way that similar data rows are mapped to similar or the same label. For example, we are building SPAM filter for email messages. We have a lot of email messages, some of which are marked as SPAM and some as INBOX. We can build a model, which learns to identify the SPAM messages. The messages to be marked as SPAM will be in some way similar to those, which are already marked as SPAM. The concept of similarity is vitally important for machine learning. In the real world, the concept of similarity is very specific to the subject matter and it depends on our knowledge.