Danïel van der Wallen

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Although there is a growing need for multi-relational data mining solutions in KDD, the use of obvious candidates from the field of Inductive Logic Programming (ILP) has been limited. In our view this is mainly due to the variation in ILP engines, especially with respect to input specification, as well as the limited attention for relational database(More)
This paper describes experiments in applying data mining techniques to historical data collected by network monitoring agents. Large amounts of performance data, including network, system, and application performance data, are collected and stored by monitoring agents. Data mining algorithms analyze the data and codify it into usable knowledge. We show, via(More)
  • Vimalkumar B. Vaghela, Kalpesh H. Vandra, +5 authors Ramon J. quotTop-down
  • 2012
As an important task of relational database, relational classification can directly classify the data that involve multiple relations from a relational database and have more advantages than propositional data mining approaches. The information age has provided us with huge data repositories which cannot longer be analyzed manually. Most available existing(More)
Although there is a growing need for multi-relational data mining solutions in KDD, the use of obvious candidates from the field of Inductive Logic Programming (ILP) has been limited. In our view this is mainly due to the variation in ILP engines, especially with respect to input specification, as well as the limited attention for relational database(More)
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