402 citations · 913 across the 36 of their papers we have counts for
7 papers · 1 filter
Keeping it Short and Simple: Summarising Complex Event Sequences with Multivariate Patterns
Roel Bertens, Jilles Vreeken, Arno Siebes
We study how to obtain concise descriptions of discrete multivariate sequential data. In particular, how to do so in terms of rich multivariate sequential patterns that can capture…
Beauty and Brains: Detecting Anomalous Pattern Co-Occurrences
Roel Bertens, Jilles Vreeken, Arno Siebes
Our world is filled with both beautiful and brainy people, but how often does a Nobel Prize winner also wins a beauty pageant? Let us assume that someone who is both very beautiful…
Universal Dependency Analysis
Hoang-Vu Nguyen, Jilles Vreeken
Most data is multi-dimensional. Discovering whether any subset of dimensions, or subspaces, of such data is significantly correlated is a core task in data mining. To do so, we req…
Linear-time Detection of Non-linear Changes in Massively High Dimensional Time Series
Hoang-Vu Nguyen, Jilles Vreeken
Change detection in multivariate time series has applications in many domains, including health care and network monitoring. A common approach to detect changes is to compare the d…
Flexibly Mining Better Subgroups
Hoang-Vu Nguyen, Jilles Vreeken
In subgroup discovery, also known as supervised pattern mining, discovering high quality one-dimensional subgroups and refinements of these is a crucial task. For nominal attribute…
Canonical Divergence Analysis
Hoang-Vu Nguyen, Jilles Vreeken
We aim to analyze the relation between two random vectors that may potentially have both different number of attributes as well as realizations, and which may even not have a joint…
Seeing the Forest through the Trees: Adaptive Local Exploration of Large Graphs
Robert Pienta, Zhiyuan Lin, Minsuk Kahng +5
Visualization is a powerful paradigm for exploratory data analysis. Visualizing large graphs, however, often results in a meaningless hairball. In this paper, we propose a differen…