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Found 13 papers, 1 papers with code
The Birkhoff completion of finite lattices
We introduce the Birkhoff completion as the smallest distributive lattice in which a given finite lattice can be embedded as semi-lattice.
Conceptual Mapping of Controversies
With our work, we contribute towards a qualitative analysis of the discourse on controversies in online news media.
The Geometric Structure of Topic Models
We introduce and demonstrate the applicability of our approach based on a topic model derived from a corpus of scientific papers taken from 32 top machine learning venues.
Automatic Textual Explanations of Concept Lattices
Our method is based on the general notion of ordinal motifs in lattices for the special case of standard scales.
Ordinal Motifs in Lattices
Lattices are a commonly used structure for the representation and analysis of relational and ontological knowledge.
Scaling Dimension
Conceptual Scaling is a useful standard tool in Formal Concept Analysis and beyond.
Conceptual Views on Tree Ensemble Classifiers
Random Forests and related tree-based methods are popular for supervised learning from table based data.
Formal Conceptual Views in Neural Networks
Explaining neural network models is a challenging task that remains unsolved in its entirety to this day.
Research Topic Flows in Co-Authorship Networks
Based on a multi-graph and a topic model, our proposed network structure accounts for intratopic as well as intertopic flows.
Quantifying the Conceptual Error in Dimensionality Reduction
Dimension reduction of data sets is a standard problem in the realm of machine learning and knowledge reasoning.
Exploring Scale-Measures of Data Sets
Measurement is a fundamental building block of numerous scientific models and their creation.
On the Lattice of Conceptual Measurements
We present a novel approach for data set scaling based on scale-measures from formal concept analysis, i. e., continuous maps between closure systems, and derive a canonical representation.
Knowledge Cores in Large Formal Contexts
Knowledge computation tasks are often infeasible for large data sets.
