activity
20202024
most citedResearch Topic Flows in Co-Authorship Networks

20 citations · 66 across the 10 of their papers we have counts for

collaborators
Showing cs.AIShow all

6 papers · 1 filter

cs.AI2024★ 1 cited

The Geometric Structure of Topic Models

Johannes Hirth, Tom Hanika

Topic models are a popular tool for clustering and analyzing textual data. They allow texts to be classified on the basis of their affiliation to the previously calculated topics.…

cs.AI2023★ 1 cited

Automatic Textual Explanations of Concept Lattices

Johannes Hirth, Viktoria Horn, Gerd Stumme +1

Lattices and their order diagrams are an essential tool for communicating knowledge and insights about data. This is in particular true when applying Formal Concept Analysis. Such…

cs.AI2023★ 3 cited

Ordinal Motifs in Lattices

Johannes Hirth, Viktoria Horn, Gerd Stumme +1

Lattices are a commonly used structure for the representation and analysis of relational and ontological knowledge. In particular, the analysis of these requires a decomposition of…

cs.AI2021★ 3 cited

Exploring Scale-Measures of Data Sets

Tom Hanika, Johannes Hirth

Measurement is a fundamental building block of numerous scientific models and their creation. This is in particular true for data driven science. Due to the high complexity and siz…

cs.AI2020★ 12 cited

On the Lattice of Conceptual Measurements

Tom Hanika, Johannes Hirth

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 represe…

cs.AI2020★ 9 cited

Knowledge Cores in Large Formal Contexts

Tom Hanika, Johannes Hirth

Knowledge computation tasks are often infeasible for large data sets. This is in particular true when deriving knowledge bases in formal concept analysis (FCA). Hence, it is essent…