Titlebook: Database and Expert Systems Applications; 29th International C Sven Hartmann,Hui Ma,Roland R. Wagner Conference proceedings 2018 Springer N

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Arkadi Berezovski,Mihhail Berezovskitegration of data relationships by (a) generating meaningful correctness probabilities for claims of data items, and (b) ensuring that the multiple correct claims output by the fusion models were consistent with each other. Our approach outperforms state-of-the-art algorithms that consider the presence of relationships over claims of data items.

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https://doi.org/10.1007/978-3-319-12670-8examine more lightweight data marts in an infrastructure which can support on-demand queries. We focus on the construction of data marts which combine both enterprise and web data, and present an evaluation which verifies the transformation process from source to data mart.

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Parameter Free Mixed-Type Density-Based Clusteringappropriate for both categorical and numerical attributes. However setting the parameters regarding any parametric clustering algorithm could be another issue. Therefore we employ minimum description length principle to automate this process.

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Combining Web and Enterprise Data for Lightweight Data Mart Constructionexamine more lightweight data marts in an infrastructure which can support on-demand queries. We focus on the construction of data marts which combine both enterprise and web data, and present an evaluation which verifies the transformation process from source to data mart.

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0302-9743 Expert Systems Applications, DEXA 2018, held in Regensburg, Germany, in September 2018..The 35 revised full papers presented together with 40 short papers were carefully reviewed and selected from 160 submissions. The papers of the first volume discuss a range of topics including: Big data analytics