Things like topic recognition, entity and reference linking/disambiguation, synonym/paraphase are well researched tasks with purpose-made datasets for competitions like TREC. The most common approaches will be to choose a word embedding (one of the word2vec or Glove are good starts) and run that into a CNN or RNN variant: https://arxiv.org/abs/1702.01923
probably if you search arxiv and the ACL anthology you should find good lit searches/historical summaries: http://aclweb.org/anthology/ Karpathy's arxiv sanity preserver is a big help. You can put together a list of maybe a few dozen twitter accounts and hashtags to watch, that'll keep you pretty current.
Comments
Things like topic recognition, entity and reference linking/disambiguation, synonym/paraphase are well researched tasks with purpose-made datasets for competitions like TREC. The most common approaches will be to choose a word embedding (one of the word2vec or Glove are good starts) and run that into a CNN or RNN variant: https://arxiv.org/abs/1702.01923
https://arxiv.org/abs/1611.09100
https://metamind.io/research/learning-when-to-skim-and-when-...
https://arxiv.org/abs/1611.06792
https://arxiv.org/abs/1611.03305
probably if you search arxiv and the ACL anthology you should find good lit searches/historical summaries: http://aclweb.org/anthology/ Karpathy's arxiv sanity preserver is a big help. You can put together a list of maybe a few dozen twitter accounts and hashtags to watch, that'll keep you pretty current.