—Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open rese...
Abstract. The concept of similarity is fundamentally important in almost every scientific field. Clustering, distance-based outlier detection, classification, regression and sea...
A student is said to have committed a careless error when a student’s answer is wrong despite the fact that he or she knows the answer (Clements, 1982). In this paper, educationa...
Maria Ofelia Clarissa Z. San Pedro, Ryan Shaun Joa...
Traditional data mining techniques have been extensively applied to find interesting patterns, build descriptive and predictive models from large volumes of data accumulated throug...
Mykola Pechenizkiy, Nikola Trcka, Ekaterina Vasily...
As data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the req...
: Data warehousing and Online Analytical Processing (OLAP) technologies are now moving onto handling complex data that mostly originate from the web. However, integrating such data...
Large scale production computing grids introduce new challenges in debugging and troubleshooting. A user that submits a workload consisting of tens of thousands of jobs to a grid ...
Data mining is the analysis of experimental datasets to extract trends and relationships that can be meaningful for the user. In genetic studies these techniques have revealed inte...
Linda Fiaschi, Jonathan M. Garibaldi, Natalio Kras...
In the recent years, our ability of collecting information rapidly increases and huge databases that change over time in a high frequency have been developed. On the other hand, th...