Constraints applied on classic frequent patterns are too strict and may cause interesting patterns to be missed. Hence, researchers have proposed to mine a more relaxed version of...
Mining graph patterns in large networks is critical to a variety of applications such as malware detection and biological module discovery. However, frequent subgraphs are often i...
The usual data mining setting uses the full amount of data to derive patterns for different purposes. Taking cues from machine learning techniques, we explore ways to divide the d...
Sequence labeling is the task of assigning a label sequence to an observation sequence. Since many methods to solve this problem depend on the specification of predictive features...
In the last years there has been a huge growth and consolidation of the Data Mining field. Some efforts are being done that seek the establishment of standards in the area. Includ...