Order is one of the main instruments to measure the relationship between...
Lattices and their order diagrams are an essential tool for communicatin...
Lattices are a commonly used structure for the representation and analys...
Real-world datasets are often of high dimension and effected by the curs...
Conceptual Scaling is a useful standard tool in Formal Concept Analysis ...
Random Forests and related tree-based methods are popular for supervised...
Induced bipartite subgraphs of maximal vertex cardinality are an essenti...
The concept of dimension is essential to grasp the complexity of data. A...
Explaining neural network models is a challenging task that remains unso...
In scientometrics, scientific collaboration is often analyzed by means o...
Steadily growing amounts of information, such as annually published
scie...
Selecting the best scientific venue (i.e., conference/journal) for the
s...
The ubiquitous presence of WiFi access points and mobile devices capable...
Dimension reduction of data sets is a standard problem in the realm of
m...
Measurement is a fundamental building block of numerous scientific model...
We present a novel approach for data set scaling based on scale-measures...
The annual number of publications at scientific venues, for example,
con...
Knowledge computation tasks are often infeasible for large data sets. Th...
Embedding large and high dimensional data into low dimensional vector sp...
A large amount of data accommodated in knowledge graphs (KG) is actually...
Order diagrams are an important tool to visualize the complex structure ...
The field of collaborative interactive learning (CIL) aims at developing...
Concept lattice drawings are an important tool to visualize complex rela...
Knowledge graphs have recently become the state-of-the-art tool for
repr...
Computing conceptual structures, like formal concept lattices, is in the...
We suggest an improved way to randomly generate formal contexts based on...
For localization and mapping of indoor environments through WiFi signals...
We propose an algorithm for learning the Horn envelope of an arbitrary d...
The curse of dimensionality in the realm of association rules is twofold...
Geometric analysis is a very capable theory to understand the influence ...
In domains with high knowledge distribution a natural objective is to cr...
We revisit the notion of probably approximately correct implication base...