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Term Indexing [electronic resource] / edited by Peter Graf.

Contributor(s): Material type: TextTextSeries: Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence ; 1053Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 1995Description: XIV, 294 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540498735
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TJ210.2-211.495
Online resources:
Contents:
Preliminaries -- Fundamental data structures and algorithms -- Attribute-based indexing -- Set-based indexing -- Tree-based indexing -- Comparison of indexing techniques -- Indexing in theorem provers -- Summary.
In: Springer eBooksSummary: Term indexing supports the construction of efficient automated reasoning systems, as e.g. automated theorem provers, by allowing rapid access to first order predicate calculus terms with specific properties. This monograph provides a comprehensive, well-written survey on term indexing in general and presents new indexing techniques for the retrieval and maintenance of data that help to overcome program degradation in automated reasoning systems. Theoretical foundations and applicational aspects are treated in detail; finally the PURR prover for parallel unit resulting resolution is discussed to demonstrate the importance of careful implementations.
Item type: E-BOOKS
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IMSc Library Link to resource Available EBK6899

Preliminaries -- Fundamental data structures and algorithms -- Attribute-based indexing -- Set-based indexing -- Tree-based indexing -- Comparison of indexing techniques -- Indexing in theorem provers -- Summary.

Term indexing supports the construction of efficient automated reasoning systems, as e.g. automated theorem provers, by allowing rapid access to first order predicate calculus terms with specific properties. This monograph provides a comprehensive, well-written survey on term indexing in general and presents new indexing techniques for the retrieval and maintenance of data that help to overcome program degradation in automated reasoning systems. Theoretical foundations and applicational aspects are treated in detail; finally the PURR prover for parallel unit resulting resolution is discussed to demonstrate the importance of careful implementations.

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The Institute of Mathematical Sciences, Chennai, India