Natural Language Processing — Fundamentals and Projects

Natural Language Processing (NLP) is a sub-area of Artificial Intelligence (AI) concerning the interaction of humans and computers.

Researches about NLP started on 50’s with Alan Turing’s tests of computer intelligence. ELIZA was the first NLP Program simulating a conversation between a patient and psychotherapist. The creation of Eliza is a remarkable step in the history of IA and it’s considered the first Chatterbot.

What can we do with NLP?

1. Automatic Summarization;
2. Translation;
3. Named Entity Recognition;
4. Relationship Extraction;
5. Sentiment Analysis;
6. Speech Recognition and more…

Practice example:

1. Social media analysis is a good example. Conversations are tracked online to understand what customers are saying, and glean insight into user behavior.

“One of the most compelling ways NLP offers valuable intelligence is by tracking sentiment — the tone of a written message (tweet, Facebook update, etc.) — and tag that text as positive, negative or neutral.”

2. Facebook uses to track trending topics and popular hashtags.

“Hashtags and topics are two different ways of grouping and participating in conversations,” Chris Struhar, a software engineer on News Feed, said in How Facebook Built Trending Topics With Natural Language Processing. “So don’t think Facebook won’t recognize a string as a topic without a hashtag in front of it. Rather, it’s all about NLP: natural language processing. Ain’t nothing natural about a hashtag, so Facebook instead parses strings and figures out which strings are referring to nodes — objects in the network. We look at the text, and we try to understand what that was about.”

OK. How computers can understand us?

ALGORITHMS AND MACHINE LEARNING

So. For now let’s drink a water and continue soon. The next chapter will be really amazing and deep about NLP techniques and ML approaches.