72 citations · 760 across the 54 of their papers we have counts for
9 papers · 1 filter
Finding Favourite Tuples on Data Streams with Provably Few Comparisons
Guangyi Zhang, Nikolaj Tatti, Aristides Gionis
One of the most fundamental tasks in data science is to assist a user with unknown preferences in finding high-utility tuples within a large database. To accurately elicit the unkn…
Mining Closed Strict Episodes
Nikolaj Tatti, Boris Cule
Discovering patterns in a sequence is an important aspect of data mining. One popular choice of such patterns are episodes, patterns in sequential data describing events that often…
Mining Closed Episodes with Simultaneous Events
Nikolaj Tatti, Boris Cule
Sequential pattern discovery is a well-studied field in data mining. Episodes are sequential patterns describing events that often occur in the vicinity of each other. Episodes can…
Probably the Best Itemsets
Nikolaj Tatti
One of the main current challenges in itemset mining is to discover a small set of high-quality itemsets. In this paper we propose a new and general approach for measuring the qual…
Comparing Apples and Oranges: Measuring Differences between Exploratory Data Mining Results
Nikolaj Tatti, Jilles Vreeken
Deciding whether the results of two different mining algorithms provide significantly different information is an important, yet understudied, open problem in exploratory data mini…
Finding Robust Itemsets Under Subsampling
Nikolaj Tatti, Fabian Moerchen, Toon Calders
Mining frequent patterns is plagued by the problem of pattern explosion making pattern reduction techniques a key challenge in pattern mining. In this paper we propose a novel theo…
Mining Periodic Patterns with a MDL Criterion
Esther Galbrun, Peggy Cellier, Nikolaj Tatti +2
The quantity of event logs available is increasing rapidly, be they produced by industrial processes, computing systems, or life tracking, for instance. It is thus important to des…
Generating Realistic Synthetic Population Datasets
Hao Wu, Yue Ning, Prithwish Chakraborty +3
Modern studies of societal phenomena rely on the availability of large datasets capturing attributes and activities of synthetic, city-level, populations. For instance, in epidemio…
Interactive Discovery of Coordinated Relationship Chains with Maximum Entropy Models
Hao Wu, Maoyuan Sun, Peng Mi +3
Modern visual analytic tools promote human-in-the-loop analysis but are limited in their ability to direct the user toward interesting and promising directions of study. This probl…