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Author Malerba, Donato ♦ Esposito, Floriana ♦ Lisi, Francesca A.
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword First-order Logic ♦ Spatial Data ♦ Onfirst-order Logic Description ♦ Feature Extraction ♦ Inductive Logic Programming ♦ Thepattern Discovery Algorithm ♦ Byan Initial Step ♦ Frequent Pattern Discovery ♦ Algorithm Spada Onspatial Data ♦ Inthis Paper ♦ Maspatial Database ♦ Semantics Andinference Rule ♦ Several Extension ♦ Recent Time ♦ Algorithm Benefit ♦ Italian Province ♦ Ilp Framework Forfrequent Pattern Discovery ♦ Hierarchical Structure ♦ Task-relevant Geographic Layer ♦ Many Promising Application ♦ Data Mining Method ♦ Logical Framework ♦ Preliminary Result ♦ Available Background Owledge ♦ Spatial Domain ♦ Advanced Database
Description In recent times, several extensions f data mining methods and techniques have been explored aiming at dealing with advanced databases. Many promising applications of inductive logic programming (ILP) to knowledge discovery in databases have also emerged inorder to benefit from semantics andinference rules of first-order logic. Inthis paper, an ILP framework forfrequent pattern discovery in spatial data is presented. Thepattern discovery algorithm operates onfirst-order logic descriptions c mputed byan initial step of feature extraction fr maspatial database. The algorithm benefits ofthe available background k owledge on the spatial domain and systematically explores the hierarchical structure of task-relevant geographic layers. Preliminary results have been obtained by running the algorithm SPADA onspatial data from an Italian province. 1
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2001-01-01
Publisher Institution Proc. of the 5th Int. Conf. KDD