Natural Language Processing (NLP) is a field of computer science and linguistics concerned with the interactions between computers and human (natural) languages. NLP deals with several tasks, such as text classification, text segmentation, parsing, and machine translation.
Importance of NLP
NLP is a key technology for many applications such as:
- Understanding customer sentiment from social media and review sites
- Automated chatbots
- Voice recognition and voice search
- Machine translation
- Generating automatic transcripts of audio and video content
Disadvantages of NLP
NLP can be computationally intensive, making it difficult to scale. It can also be difficult to train NLP models due to the lack of data.
Tools Used to Perform NLP
There are several different tools that can be used to perform NLP tasks, including:
- tokenizers
- parsers
- stemmers
- lemmatizers
- stop words
- part-of-speech taggers
- named entity recognition tools
NLP and Related Terms
NLP is closely related to the field of artificial intelligence (AI) and has many applications in areas such as computational linguistics, information retrieval, and natural language generation.
The term “natural language processing” is sometimes used interchangeably with “computational linguistics.” However, NLP is a more specific field that focuses on the interactions between computers and human languages, while computational linguistics is a more general field that deals with the use of computers to process and analyze linguistic data.
NLP is also sometimes used interchangeably with “text analytics.” However, text analytics is a more general field that deals with the use of computers to analyze and extract information from textual data. NLP is concerned specifically with the processing of natural language data.