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Auflistung nach Schlagwort "Association rule mining"

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  • Textdokument
    Improving a Rule-based Fraud Detection System with Classification Based on Association Rule Mining
    (INFORMATIK 2021, 2021) Baumann, Michaela
    Improving a Rule-based Fraud Detection System with Classification Based on Association Rule MiningThe detection of fraudulent insurance claims is a great challenge for insurance companies. Although the detection possibilities are getting better and better, fraudsters do not hesitate also using newer and more sophisticated methods. Apart from establishing new fraud detection systems, also the existing systems need to be updated and improved as best as possible. One common detection system is a rule-based expert system that checks predefined rules and gives alerts when certain conditions are met. Usually, the rules are treated separately and correlations within the rules are considered insufficiently. The work at hand describes how the classification based on association rule mining is used for improving such rule-based systems by bringing in relations between pairs of rules. The rule weights are determined through a genetic optimizer.
  • Zeitschriftenartikel
    Improving RDF Data Through Association Rule Mining
    (Datenbank-Spektrum: Vol. 13, No. 2, 2013) Abedjan, Ziawasch; Naumann, Felix
    Linked Open Data comprises very many and often large public data sets, which are mostly presented in the Rdf triple structure of subject, predicate, and object. However, the heterogeneity of available open data requires significant integration steps before it can be used in applications. A promising and novel technique to explore such data is the use of association rule mining. We introduce “mining configurations”, which allow us to mine Rdf data sets in various ways. Different configurations enable us to identify schema and value dependencies that in combination result in interesting use cases. We present rule-based approaches for predicate suggestion, data enrichment, ontology improvement, and query relaxation. On the one hand we prevent inconsistencies in the data through predicate suggestion, enrichment with missing facts, and alignment of the corresponding ontology. On the other hand we support users to handle inconsistencies during query formulation through predicate expansion techniques. Based on these approaches, we show that association rule mining benefits the integration and usability of Rdf data.