Automatic construction and refinement of a class hierarchy over semistructured data

作者: Nathalie Pernelle , Marie-Christine Rousset , Veronique Ventos

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摘要: In many applications, it becomes crucial to help users access a huge amount of data by clustering them in small number classes described at an appropriate level abstraction. this paper, we present approach based on the use two languages description for automatic semistructured data. The rst language has high power abstraction and guides construction lattice covering whole set second classes, more expressive precise, is basis re nement part that user wants focus on. Our been implemented experimented real setting GAEL project 1 which aims building exible electronic catalogs organized as hierarchy products. experiments have conducted coming from C/Net (http://www.cnet.com) catalog computer

参考文章(13)
Gilles Bisson, Conceptual clustering in a first order logic representation european conference on artificial intelligence. pp. 458- 462 ,(1992)
Jean-Gabriel Ganascia, TDIS : an Algebraic Formalization. international joint conference on artificial intelligence. pp. 1008- 1015 ,(1993)
Henry Soldano, Pierre Brézellec, Tabata: A Learning Algorithm Performing a Bidirectional Search in a Reduced Search Space Using a Tabu Strategy. european conference on artificial intelligence. pp. 420- 424 ,(1998)
Ramakrishnan Srikant, Rakesh Agrawal, Fast Algorithms for Mining Association Rules in Large Databases very large data bases. pp. 487- 499 ,(1994)
Jörg-Uwe Kietz, Katharina Morik, A Polynomial Approach to the Constructive Induction of Structural Knowledge Machine Learning. ,vol. 14, pp. 193- 217 ,(1994) , 10.1023/A:1022626200450
Mathias Kirsten, Stefan Wrobel, Extending K-Means Clustering to First-Order Representations inductive logic programming. pp. 112- 129 ,(2000) , 10.1007/3-540-44960-4_7
Ryszard S. Michalski, Robert E. Stepp, Learning from Observation: Conceptual Clustering Machine Learning. pp. 331- 363 ,(1983) , 10.1007/978-3-662-12405-5_11
William W. Cohen, Haym Hirsh, Learning the classic description logic: theoretical and experimental results principles of knowledge representation and reasoning. pp. 121- 133 ,(1994) , 10.1016/B978-1-4832-1452-8.50108-1
Franz Baader, Ralf Molitor, Ralf Kusters, Computing Least Common Subsumers in Description Logics with Existential Restrictions international joint conference on artificial intelligence. pp. 96- 101 ,(1999)
Luc De Raedt, Hendrik Blockeel, Jan Ramon, Top-Down Induction of Clustering Trees international conference on machine learning. pp. 55- 63 ,(1998)