Natural Language Processing in Artificial Intelligence Sigmoidal

Back in the days when a Neural Network was that scary, hard-to-learn thing which was rather a mathematical curiosity than a powerful Machine Learning or Artificial Intelligence tool - there were surprisingly many relatively successful applications of classical data mining algorithms in Natural Language Processing (NLP) domain. It seemed that problems like spam filtering or Part of Speech Tagging could be solved using rather easy and understandable models. But not every problem can be solved this way. Simple models fail to properly capture linguistic subtleties like irony (although humans often fail at that one too), idioms or context. Algorithms based on overall summarization (e.g.