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KDD
1995
ACM
167views Data Mining» more  KDD 1995»
13 years 11 months ago
Efficient Algorithms for Attribute-Oriented Induction
Data mining or knowledge discovery in databasesis the search for relationships and global patterns that exist but are hidden in large databases.Many different methodshave been pro...
Hoi-Yee Hwang, Ada Wai-Chee Fu
AIIA
2005
Springer
14 years 1 months ago
A Semantic Kernel to Exploit Linguistic Knowledge
Abstract. Improving accuracy in Information Retrieval tasks via semantic information is a complex problem characterized by three main aspects: the document representation model, th...
Roberto Basili, Marco Cammisa, Alessandro Moschitt...
CINQ
2004
Springer
157views Database» more  CINQ 2004»
13 years 11 months ago
Inductive Databases and Multiple Uses of Frequent Itemsets: The cInQ Approach
Inductive databases (IDBs) have been proposed to afford the problem of knowledge discovery from huge databases. With an IDB the user/analyst performs a set of very different operat...
Jean-François Boulicaut
PKDD
1998
Springer
123views Data Mining» more  PKDD 1998»
13 years 11 months ago
Querying Inductive Databases: A Case Study on the MINE RULE Operator
Knowledge discovery in databases (KDD) is a process that can include steps like forming the data set, data transformations, discovery of patterns, searching for exceptions to a pat...
Jean-François Boulicaut, Mika Klemettinen, ...
SWAP
2008
13 years 9 months ago
A Note on the Evaluation of Inductive Concept Classification Procedures
Abstract. The limitations of deductive logic-based approaches at deriving operational knowledge from ontologies may be overcome by inductive (instancebased) methods, which are usua...
Claudia d'Amato, Nicola Fanizzi, Floriana Esposito