Networks (or graphs) appear as dominant structures in diverse domains, including
sociology, biology, neuroscience and computer science. In most of the aforementioned …

In almost every scientific field, measurements are performed over time. These observations
lead to a collection of organized data called time series. The purpose of time-series data …

Outlier detection has been a topic in statistics for centuries. Over mainly the last two
decades, there has been also an increasing interest in the database and data mining …

Ming Li Paul Vitányi Fourth Edition Page 1 An Introduction to Kolmogorov Complexity and Its
Applications Ming Li Paul Vitányi Fourth Edition Texts in Computer Science Page 2 Texts in …

As a prolific research area in data mining, subspace clustering and related problems
induced a vast quantity of proposed solutions. However, many publications compare a new …

One of the major problems in pattern mining is the explosion of the number of results. Tight
constraints reveal only common knowledge, while loose constraints lead to an explosion in …

Seriation is an exploratory combinatorial data analysis technique to reorder objects into a
sequence along a one‐dimensional continuum so that it best reveals regularity and …

How can we succinctly describe a million-node graph with a few simple sentences? How
can we measure the 'importance'of a set of discovered subgraphs in a large graph? These …

Subspace clustering finds sets of objects that are homogeneous in subspaces of high-
dimensional datasets, and has been successfully applied in many domains. In recent years …

Pattern mining based on data compression has been successfully applied in many data
mining tasks. For itemset data, the Krimp algorithm based on the minimum description length …