We study the problem of mining frequent value sets from a large sensor network. We discuss how sensor stream data could be represented that facilitates efficient online mining and ...
Data mining has been defined as the non- trivial extraction of implicit, previously unknown and potentially useful information from data. Association mining is one of the important...
Peter Bollmann-Sdorra, Aladdin Hafez, Vijay V. Rag...
We study the inference on the interesting association rules. Then we define the concept of the representative basis for interesting association rules extracted from a dataset D, a...
An important problem that arises during the data mining process in many new emerging application domains is mining data with temporal dependencies. One such application domain is a...
Transduction is an inference mechanism “from particular to particular”. Its application to classification tasks implies the use of both labeled (training) data and unlabeled (...