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KDD
1995
ACM
167views Data Mining» more  KDD 1995»
15 years 1 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
15 years 3 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»
15 years 1 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»
15 years 1 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
14 years 11 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