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Mining graph data / (2007)

Cook, Diane J. ; Holder, Lawrence B.

Hoboken, N.J :Wiley,

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Titel: Mining graph data /

Beteiligte Person(en): Cook, Diane J. , Holder, Lawrence B.

Verlag: Hoboken, N.J :Wiley,

Erscheinungsjahr: 2007

Seiten: XIX, 479 S. : , Ill., graph. Darst.

ISBN: 0-471-73190-0 , 978-0-471-73190-0

Materialart: Buch

Sprache: Englisch

URL: Inhaltsverzeichnis

URL: Table of contents only

URL: Publisher description

URL: Contributor biographical information

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Zuse-Institut Berlin

Digitale Medien

Experimentation-Driven Knowledge Acquisition for Planning (1999)

Tae, Kang Soo ; Cook, Diane J. ; Holder, Lawrence B.

Boston, USA and Oxford, UK : Blackwell Publishers Inc

Computational intelligence 15 (1999), S. 0

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ISSN: 1467-8640

Quelle: Blackwell Publishing Journal Backfiles 1879-2005

Thema: Informatik

Notizen: Knowledge engineering for planning is expensive and the resulting knowledge can be imperfect. To autonomously learn a plan operator definition from environmental feedback, our learning system WISER explores an instantiated literal space using a breadth-first search technique. Each node of the search tree represents a state, a unique subset of the instantiated literal space. A state at the root node is called a seed state. WISER can generate seed states with or without utilizing imperfect expert knowledge. WISER experiments with an operator at each node. The positive state, in which an operator can be successfully executed, constitutes initial preconditions of an operator. We analyze the number of required experiments as a function of the number of missing preconditions in a seed state. We introduce a naive domain assumption to test only a subset of the exponential state space. Since breadth-first search is expensive, WISER introduces two search techniques to reorder literals at each level of the search tree. We demonstrate performance improvement using the naive domain assumption and literal-ordering heuristics. To learn the effects of an operator, WISER computes the delta state, composed of the add list and the delete list, and parameterizes it. Unlike previous systems, WISER can handle unbound objects in the delta state. We show that machine-generated effects definitions are often simpler in representation than expert-provided definitions.

Materialart: Digitale Medien

URL: http://dx.doi.org/10.1111/0824-7935.00093

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Digitale Medien

Knowledge discovery from structural data (1995)

Cook, Diane J. ; Holder, Lawrence B. ; Djoko, Surnjani

Springer

Journal of intelligent information systems 5 (1995), S. 229-248

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ISSN: 1573-7675

Schlagwort(e): machine discovery ; data mining ; data compression ; inexact graph match ; scene analysis ; chemical analysis

Quelle: Springer Online Journal Archives 1860-2000

Thema: Informatik

Notizen: Abstract Discovering repetitive substructure in a structural database improves the ability to interpret and compress the data. This paper describes the Subdue system that uses domain-independent and domain-dependent heuristics to find interesting and repetitive structures in structural data. This substructure discovery technique can be used to discover fuzzy concepts, compress the data description, and formulate hierarchical substructure definitions. Examples from the domains of scene analysis, chemical compound analysis, computer-aided design, and program analysis demonstrate the benefits of the discovery technique.

Materialart: Digitale Medien

URL: http://dx.doi.org/10.1007/BF00962235

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