A Framework for Object-Oriented Data Mining Based on Higher-Order Logic Programming

Data mining discovers knowledge and useful information from large amounts of data stored in databases. With the increasing popularity of object-oriented database system in advanced database applications, it is significantly important to study the data mining methods for object-oriented database. Thi...

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Veröffentlicht in:Applied Mechanics and Materials Jg. 420; H. Recent Trends in Materials and Mechanical Engineering II; S. 325 - 332
Hauptverfasser: Zhang, Zhi Ping, Wang, Li Jun, Yu, Hai Yan, Li, Lin Na
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Zurich Trans Tech Publications Ltd 01.09.2013
Schlagworte:
Data mining
Formalism
Languages
Logic programming
Object oriented
Object-oriented programming
Representations
Data Mining (DM)
Higher-Order Logic Programming
Object-Oriented Database
ISBN:3037858699, 9783037858691
ISSN:1660-9336, 1662-7482, 1662-7482
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Abstract Data mining discovers knowledge and useful information from large amounts of data stored in databases. With the increasing popularity of object-oriented database system in advanced database applications, it is significantly important to study the data mining methods for object-oriented database. This paper proposes that higher-order logic programming languages and techniques is very suitable for object-oriented data mining, and presents a framework for object-oriented data mining based on higher-order logic programming. Such a framework is inductive logic programming which adopts higher-order logic programming language Escher as knowledge representation formalism. In addition, Escher is a generalization of the attribute-value representation, thus many higher-order logic learners under this framework can be upgraded directly from corresponding propositional learners.
AbstractList Data mining discovers knowledge and useful information from large amounts of data stored in databases. With the increasing popularity of object-oriented database system in advanced database applications, it is significantly important to study the data mining methods for object-oriented database. This paper proposes that higher-order logic programming languages and techniques is very suitable for object-oriented data mining, and presents a framework for object-oriented data mining based on higher-order logic programming. Such a framework is inductive logic programming which adopts higher-order logic programming language Escher as knowledge representation formalism. In addition, Escher is a generalization of the attribute-value representation, thus many higher-order logic learners under this framework can be upgraded directly from corresponding propositional learners.
Author Zhang, Zhi Ping
Li, Lin Na
Wang, Li Jun
Yu, Hai Yan
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Higher-Order Logic Programming
Object-Oriented Database
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SubjectTerms Data mining
Formalism
Languages
Logic programming
Object oriented
Object-oriented programming
Representations
Title A Framework for Object-Oriented Data Mining Based on Higher-Order Logic Programming
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