Natural Language processing (NLP) is a field of computer science and linguistics concerned with the interactions between computers and human (natural) languages. In theory, natural-language processing is a very attractive method of human-computer interaction. Natural-language understanding is sometimes referred to as an AI-complete problem, because natural-language recognition seems to require extensive knowledge about the outside world and the ability to manipulate it.
Related Sciences, Topics and Techniques:
Major tasks in NLP:
- Automatic summarization
- Foreign language reading aid
- Foreign language writing aid
- Information extraction
- Information retrieval (IR) - IR is concerned with storing, searching and retrieving information. It is a separate field within computer science (closer to databases), but IR relies on some NLP methods (for example, stemming). Some current research and applications seek to bridge the gap between IR and NLP.
- Machine translation - Automatically translating from one human language to another.
- Named entity recognition (NER) - Given a stream of text, determining which items in the text map to proper names, such as people or places. Although in English, named entities are marked with capitalized words, many other languages do not use capitalization to distinguish named entities.
- Natural language generation
- Natural language search
- Natural language understanding
- Optical character recognition
- anaphora resolution
- Query expansion
- Question answering - Given a human language question, the task of producing a human-language answer. The question may be a closed-ended (such as "What is the capital of Canada?") or open-ended (such as "What is the meaning of life?").
- Speech recognition - Given a sound clip of a person or people speaking, the task of producing a text dictation of the speaker(s). (The opposite of text to speech.)
- Spoken dialogue system
- Stemming
- Text simplification
- Text-to-speech
- Text-proofing
There is many applications that serve Arabic language.