We present a theoretical analysis for prediction algorithms based on association rules. As
part of this analysis, we introduce a problem for which rules are particularly natural, called" …

Frequent subgraph mining has always been an important issue in data mining. Several
frequent graph mining methods have been developed for mining graph transactions …

The increase in the photovoltaic generation on distribution grids may create problems, such
as voltage-violations. To gain situational awareness for system operation, eg, adjusting the …

The cortical thickness of long bones can be an effective indicator of locomotor modes and
other stresses encountered by bone. Felids and canids are two carnivoran families that have …

We present a theoretical framework for the problem of “sequential event prediction” where
events in a sequence are revealed one by one, and the goal is to determine which event will …

In the present time, Graph Mining has become the most research-oriented field in the
advance technologies for its importance in many areas, such as citation graphs, web data …

We present a framework and generalization analysis for the use of association rules in the
setting of supervised learning. We are specifically interested in a sequential event prediction …

The increase in the photovoltaic (PV) generation on distribution grids may cause reverse
power flows and challenges such as service voltage violations and transformer overloading …

In this demonstration, we aim to present the ACSM prototype that deals with the discovery of
frequent patterns in the context of flow management problems. One important issue while …