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CSA3050 Natural Language Algorithms

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... of these s taken from J Nivre, University of Gotheborg, Sweden ... Applied. Computer Science. Algorithms. Compiling Techniques. Artificial Intelligence ... – PowerPoint PPT presentation

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Title: CSA3050 Natural Language Algorithms


1
CSA3050Natural Language Algorithms
  • Introduction
  • and
  • Overview

2
Course Information
  • Course Websitewww.cs.um.edu.mt/mros/csa3050
  • Reference TextJurafsky and Martin

3
Acknowledgement
  • Material for some of these slides taken from J
    Nivre, University of Gotheborg, Sweden

4
Why Language and Computers
  • Engineering
  • NLP is concerned with the design and
    implementation of effective NL input and output
    components for computational systems (Robert Dale
    2000)
  • Scientific
  • The use of computers for linguistic research and
    applications

5
NLP is Interdisciplinary
  • Linguistics
  • Theoretical
  • Applied
  • Computer Science
  • Algorithms
  • Compiling Techniques
  • Artificial Intelligence
  • Understanding, reasoning
  • Intelligent Action

6
Uszkoreits (2000) Five Points
  • Solving the human language puzzle
  • by implementing complex theories directly
  • Teaching computers to communicate with people
  • by exploiting natural modes of communication
  • Friendly software should listen and speak
  • through development of multimodal communication
  • Machines can help people communicate with each
    other.
  • by developing multilingual applications
  • Language is the fabric of the web
  • through language technology for knowledge
    management

7
Application Areas
  • Document Processing
  • Classification
  • Summarisation
  • Information Extraction
  • Question Answering
  • Information Retrieval
  • Dialogue
  • Multilinguality
  • Machine Translation
  • Translation tools
  • Multimodality
  • speech
  • intonation
  • image

8
Basic Problems
  • Analysis
  • Conversion of NL input to internal
    representations
  • Generation
  • Conversion of internal representations to NL
    output
  • Issues
  • What kind of input/output/representations
  • Evaluation
  • Learning

9
Levels of Linguistic Knowledge
  • Phonetics/Phonology sound structure
  • Morphology word structure
  • Syntax sentence structure
  • Semantics meanings
  • Pragmatics use of language in context
  • Discourse paragraphs, texts, dialogues

10
Ambiguity
  • Morpho-SyntacticWe saw her duck
  • Lexical SemanticThey went to the bank
  • Structural semanticYoung men and women
  • ReferentialShe did it
  • PragmaticCan you pass the salt

11
Ways of Studying NLP
  • By ApplicationMT, IE, IR etc.
  • By Approachrational vs. empirical
  • By Linguistic Levelmorphology, syntax etc.
  • By Algorithm

12
Algorithms
  • State Machines
  • automata and transducers
  • Rule Systems
  • regular and context free grammars
  • Search
  • top-down/bottom-up parsing
  • Probabilistic algorithms

13
Approach in this Course
  • Words
  • Morphological Processing
  • Finite State Algorithms
  • Stemming
  • Sentences
  • Parsing
  • Generation
  • Texts
  • Preprocessing
  • Tagging
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