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Best NLP technique for extracting information from the text

5 years ago in Data collection By Riya N

PhD Data

Could someone tell me the best technique used for extracting information from the text in natural language processing field?

All Answers (3 Answers In All)

By Payal G Answered 5 years ago

You can either use sentiment analysis or named entity recognition. Sentiment analysis is widely used technique in NLP. The outcome of sentiment analysis is a 3-point scale i.e. neutral/positive/negative. In crucial cases the output could be a numeric score that could be bucketed into as sections as required. Named entity recognition useful technique in NLP in extracting the entities from the text. It highlights the references and concepts in the text.

By Rohini Singh Answered 5 years ago

Text summarisation is the best technique. This technique summarises large chunks of text. Two approaches are used to summarise text such as extraction and abstraction. Through extracting parts from the text, extraction method creates a summary of the text. Whereas abstraction method generates fresh text and creates summary.

By Kamlesh Meena Answered 5 years ago

Riya, if you want to identify the various aspects in the text, then use aspect mining approach. One of the easiest approaches of aspect mining is utilising a part-of-speech tagging. When used along with sentiment analysis, this approach extracts complete information from the text.