Temporal Data Mining is a core concept of Knowledge Discovery in Databases handling time-oriented data. Stateof-the-art methods are capable of preserving the temporal order of events as well as the information in between. The temporal nature of the events themselves, however, can likely be misinterpreted by current algorithms. We present a new definition of the temporal aspects of events and ex...

fuzzy rule-based classification system (frbcs) is a popular machine learning technique for classification purposes. one of the major issues when applying it on imbalanced data sets is its biased to the majority class, such that, it performs poorly in respect to the minority class. however many cases the minority classes are more important than the majority ones. in this paper, we have extended ...

Spatial data mining focuses on searching rules of the geographical statement, the structures of distribution and the spatial patterns of phenomena. However, many methods ignore the temporal information, thus, limited results describing the statement of spatial phenomena. This paper focuses on developing a mining method which directly detects spatial-temporal association rules hidden in the geog...

Mining association rules is most commonly seen among the techniques for knowledge discovery from databases (KDD). It is used to discover relationships among items or itemsets. Furthermore, temporal data mining is concerned with the analysis of temporal data and the discovery of temporal patterns and regularities. In this paper, a new concept of up-to-date patterns is proposed, which is a hybrid...

Most methods for temporal pattern mining assume that time is represented by points in a straight line starting at some initial instant. In this paper, we consider a new kind of first order temporal pattern, specified in Allen’s Temporal Interval Logic, where time is explicitly represented by intervals. We present the algorithm MILPRIT for mining temporal interval patterns, which uses variants o...

In this article we define a formalism to discover knowledge in the form of temporal rules, inferred from databases of events with a temporal dimension. The theoretical framework is based on first-order temporal logic and allows the definition of the main temporal data mining notions (event, temporal rule, constraint) in a formal way. The concepts of consistent linear time structure and general ...

Most data sources in real-life are not static but change their information in time. This evolution of data in time can give valuable insights to business analysts. Temporal data refers to data, where changes over time or temporal aspects play a central role. Temporal data denotes the evaluation of object characteristics over time. One of the main unresolved problems that arise during the data m...