Coverart for item
The Resource Probabilistic inductive logic programming : theory and applications, Luc De Raedt [and others] (eds.)

Probabilistic inductive logic programming : theory and applications, Luc De Raedt [and others] (eds.)

Label
Probabilistic inductive logic programming : theory and applications
Title
Probabilistic inductive logic programming
Title remainder
theory and applications
Statement of responsibility
Luc De Raedt [and others] (eds.)
Contributor
Subject
Language
eng
Summary
"The question, how to combine probability and logic with learning, is gaining increased attention in several disciplines, e.g., knowledge representation, reasoning about uncertainty, data mining, and machine learning. The emerging field of study is known under the names of statistical relational learning and probabilistic inductive logic programming." "This book provides an introduction to the field with an emphasis on the methods based on logic programming principles. It is concerned with formalisms and systems, implementations and applications, as well as with the theory of probabilistic inductive logic programming."--Jacket
Member of
Cataloging source
GW5XE
Dewey number
006.31
Illustrations
illustrations
Index
index present
LC call number
QA76.63
LC item number
.P69 2008eb
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorDate
1964-
http://library.link/vocab/relatedWorkOrContributorName
Raedt, Luc de
Series statement
  • LNCS sublibrary. SL 7, Artificial intelligence
  • Lecture notes in computer science,
  • Lecture notes in artificial intelligence
  • State-of-the-art survey
Series volume
4911.
http://library.link/vocab/subjectName
  • Logic programming
  • Machine learning
  • Stochastic processes
  • Informatique
  • Logic programming
  • Machine learning
  • Stochastic processes
  • Computer Science
  • Mechanical Engineering - General
  • Engineering & Applied Sciences
  • Mechanical Engineering
Label
Probabilistic inductive logic programming : theory and applications, Luc De Raedt [and others] (eds.)
Instantiates
Publication
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Probabilistic Inductive Logic Programming -- Formalisms and Systems -- Relational Sequence Learning -- Learning with Kernels and Logical Representations -- Markov Logic -- New Advances in Logic-Based Probabilistic Modeling by PRISM -- CLP(): Constraint Logic Programming for Probabilistic Knowledge -- Basic Principles of Learning Bayesian Logic Programs -- The Independent Choice Logic and Beyond -- Applications -- Protein Fold Discovery Using Stochastic Logic Programs -- Probabilistic Logic Learning from Haplotype Data -- Model Revision from Temporal Logic Properties in Computational Systems Biology -- Theory -- A Behavioral Comparison of Some Probabilistic Logic Models -- Model-Theoretic Expressivity Analysis
Control code
233973998
Dimensions
unknown
Extent
1 online resource (viii, 339 pages)
Form of item
online
Governing access note
University staff and students only. Requires University Computer Account login off-campus
Isbn
9783540786511
Lccn
2008922315
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-3-540-78652-8
Other physical details
illustrations
http://library.link/vocab/ext/overdrive/overdriveId
978-3-540-78651-1
Publisher number
12239573
Specific material designation
remote
System control number
(OCoLC)233973998
Label
Probabilistic inductive logic programming : theory and applications, Luc De Raedt [and others] (eds.)
Publication
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Probabilistic Inductive Logic Programming -- Formalisms and Systems -- Relational Sequence Learning -- Learning with Kernels and Logical Representations -- Markov Logic -- New Advances in Logic-Based Probabilistic Modeling by PRISM -- CLP(): Constraint Logic Programming for Probabilistic Knowledge -- Basic Principles of Learning Bayesian Logic Programs -- The Independent Choice Logic and Beyond -- Applications -- Protein Fold Discovery Using Stochastic Logic Programs -- Probabilistic Logic Learning from Haplotype Data -- Model Revision from Temporal Logic Properties in Computational Systems Biology -- Theory -- A Behavioral Comparison of Some Probabilistic Logic Models -- Model-Theoretic Expressivity Analysis
Control code
233973998
Dimensions
unknown
Extent
1 online resource (viii, 339 pages)
Form of item
online
Governing access note
University staff and students only. Requires University Computer Account login off-campus
Isbn
9783540786511
Lccn
2008922315
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-3-540-78652-8
Other physical details
illustrations
http://library.link/vocab/ext/overdrive/overdriveId
978-3-540-78651-1
Publisher number
12239573
Specific material designation
remote
System control number
(OCoLC)233973998

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