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Introduction To Natural Language Processing (NLP)
Natural Language Processing (NLP) can be interpreted as an advanced concept in analytics whose focus is set on the interactions between human language and computers. NLP is a diverse concept that makes use of advanced aspects in computer science, artificial intelligence, and computational linguistics.
NLP work towards understanding computer intelligence & at the same time it deals with the process of manipulating human intelligence. A precise approach in understanding & handling NLP would result in exploring new insights & patterns.
Understanding Natural Language Processing-
Natural Language Processing presents machines or computer systems with the ability analyze, understand, and derive meaning from the human language in a more effective way. With a better understanding of applications in NLP & through perfect execution of its strategies, it would make it possible for the developers to organize and structure knowledge towards performing tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation and many more.
You must be well aware of the operation of a common word processor where a text form would get treated as a mere depiction of symbols. In contrast, NLP considers a hierarchical structure of language where several words make a phrase, several phrases make a sentence and, ultimately, sentences convey ideas. As a part of its operation process, NLP executes multiple operations like correcting grammar, converting speech to text and automatically translating between languages.
Natural Language Processing Applications-
By making the human-computer interaction possible NLP works towards building applications like automatic text summarization, sentiment analysis, topic extraction, named entity recognition, parts-of-speech tagging, relationship extraction, stemming, and more.
At present, as NLP is still in its early stages of development, it is being used by the industry for common applications text mining, machine translation, and automated question answering.
Some Of The Use Cases Of NLP-
- Helps towards recognition & prediction of diseases by analyzing the electronics health records & patient’s own speech
- NLP sentiment analysis can help the businesses in understanding their customers choices & their decision drivers
- Companies that provide Email services like Google & Yahoo are making use of NLP to analyze the text in Emails that passes through their services in order to prevent spam mails even before they could enter their users inbox
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