Scalable Online Learning of Topic Models...

This talk deals with the problem of how to learn topic models from large text corpora that are constantly growing such as with online forums. As documents stream into your corpus it is much more efficient to update your already learned topic model rather than batch processing your entire corpus. Furthermore, Apache Spark can be used to perform the sequential updates in a distributed fashion. The talk will also include a discussion on how to use your learned topic model to classify the documents in your corpus based on the topics they contain.