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Natural language processing

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Natural language processing provides a way in which human interacts with computer / machines by means of voice.
"Google Search by voice is the best example " which makes use of natural language processing..

Publié dans : Technologie
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Natural language processing

  1. 1. A Seminar on Natural Language Processing Presented by Prashant Dahake Mtech 1st sem (CSE) Sub:- Artificial Intelligence G.H. Raisoni College of Engineering Nagpur Dept. of Computer Science & Engineering 2013-2014 1 1 1
  2. 2. Introduction Natural Language?  Refers to the language spoken by people, e.g. English, Japanese, as opposed to artificial languages, like C++, Java, etc. Natural Language Processing?`  NLP is the branch of computer science focused on developing systems that allow computers to communicate with people using everyday language.  NLP is related to human -computer interaction.
  3. 3.  NLP encompasses anything a computer needs to understand natural language and also generate natural language.  NLP is a subfield of artificial intelligence. Devoted to make computers “understand” statements written in human language.
  4. 4. Why Natural Language Processing? • • • • • kJfmmfj mmmvvv nnnffn333 Uj iheale eleee mnster vensi credur Baboi oi cestnitze Coovoel2^ ekk; ldsllk lkdf vnnjfj? Fgmflmllk mlfm kfre xnnn!
  5. 5. Computers Lack Knowledge! • Computers “see” text in English the same we have seen the previous text! • People have no trouble understanding language – Common sense knowledge – Reasoning capacity – Experience • Computers have – No common sense knowledge – No reasoning capacity that’s why we need natural language processing.
  6. 6. Where does it fit in the Classification? Computers Databases Robotics Information Retrieval Artificial Intelligence Algorithms Networking Search Natural Language Processing Machine Translation Language Analysis Semantics Parsing
  7. 7. Steps in natural language processing  Morphological Analysis  Syntactic Analysis  Semantic Analysis  Discourse Analysis  Pragmatic Analysis
  8. 8. Morphological analysis Individual words are analyzed into their component and nonword tokens. punctuation are separated from word . e.g carried= carry+ed Syntactic analysis .grammatical structure of sentence is analyze. . some word sequence may be rejected if they violate the rules of language . e.g syntactic analyzer reject the sentence “Boy the go the to store” Semantic analysis . determine possible meaning of sentence. . Sentence which has no meaning is rejected. . For eg “ colorless green ideas ” has no meaning.
  9. 9. Discourse Analysis . The meaning of an individual sentence may depends on the sentence that precede it and may influence the meaning of sentences that follow it. e.g “john wanted it” the word ‘it’ depends upon john. Pragmatic analysis . It derives knowledge from external commonsense information. . It means understanding purposeful use of language in situation. e.g “ DO you know what time it is?” should be interpreted as a request.
  10. 10. Application of NLP Text-based applications  searching for a certain topic in a data base .  extracting information from a large document . Dialogue based applications  answering systems.  Services provided over a telephone.  voice controlled machines (that take instructions by speech)
  11. 11. What can we expect in the FUTURE  In robotics  in car
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