Data with temporal information is constantly generated, sampled, gathered, and analyzed in different domains, such as medicine, finance, engineering, environmental sciences, and e...
Dynamic data streams are those whose underlying distribution changes over time. They occur in a number of application domains, and mining them is important for these applications....
Molecular and computational biologists develop new insights by gathering heterogeneous data from genomic databases and leveraging bioinformatics tools. Through a qualitative study...
Orit Shaer, Guy Kol, Megan Strait, Chloe Fan, Cath...
Currently statistical and artificial neural network methods dominate in data mining applications. Alternative relational (symbolic) data mining methods have shown their effectivene...
Commercial relational databases currently store vast amounts of real-world data. The data within these relational repositories are represented by multiple relations, which are int...