Statistically sound pattern discovery harnesses the rigour of statistical hypothesis testing to
overcome many of the issues that have hampered standard data mining approaches to …

Discovering causal relationships from observational data is a crucial problem and it has
applications in many research areas. The PC algorithm is the state-of-the-art constraint …

Causal discovery studies the problem of mining causal relationships between variables from
data, which is of primary interest in science. During the past decades, significant amount of …

Educational Data Mining (EDM) is an emerging inter-disciplinary research area that involves
education and computer science. EDM employs data mining tools and techniques, on large …

Determining the cause of a particular event has been a case of study for several researchers
over the years. Finding out why an event happens (its cause) means that, for example, if we …

As the world's population grows older, an increasing number of people are facing health
issues. For the elderly, living alone can be difficult and dangerous. Consequently, smart …

Uncovering causal relationships in data is a major objective of data analytics. Currently,
there is a need for scalable and automated methods for causal relationship exploration in …

Causality analysis continues to remain one of the fundamental research questions and the
ultimate objective for a tremendous amount of scientific studies. In line with the rapid …

Revealing complex relations between entities (eg, items within or between transactions) is of
great significance for business optimization, prediction, and decision making. Such relations …

Both artificial intelligence (AI) and domain knowledge from human experts play an important
role in manufacturing decision making. Smart manufacturing emphasizes a fully automated …