Search Results for author:
Found 28 papers, 4 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.
Towards Ordinal Data Science
One reason for this is the limited availability of computational resources in the last century that would have been required for ordinal computations.
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.
Maximal Ordinal Two-Factorizations
Given a formal context, an ordinal factor is a subset of its incidence relation that forms a chain in the concept lattice, i. e., a part of the dataset that corresponds to a linear order.
Greedy Discovery of Ordinal Factors
Based on such an ordinal factorization, we provide a way to discover and explain relationships between different items and attributes in the dataset.
Discovering Locally Maximal Bipartite Subgraphs
Induced bipartite subgraphs of maximal vertex cardinality are an essential concept for the analysis of graphs.
Attribute Exploration with Multiple Contradicting Partial Experts
In this paper we present an extension of attribute exploration that allows for a group of domain experts and explores their shared views.
Mapping Research Trajectories
Hence, we propose a principled approach for \emph{mapping research trajectories}, which is applicable to all kinds of scientific entities that can be represented by sets of published papers.
Towards Explainable Scientific Venue Recommendations
Selecting the best scientific venue (i. e., conference/journal) for the submission of a research article constitutes a multifaceted challenge.
LG4AV: Combining Language Models and Graph Neural Networks for Author Verification
The automatic verification of document authorships is important in various settings.
Attribute Selection using Contranominal Scales
One of the main goals of FCA is to enable humans to comprehend the information that is encapsulated in the data; however, the large size of concept lattices is a limiting factor for the feasibility of understanding the underlying structural properties.
Topological Indoor Mapping through WiFi Signals
The ubiquitous presence of WiFi access points and mobile devices capable of measuring WiFi signal strengths allow for real-world applications in indoor localization and mapping.
Force-Directed Layout of Order Diagrams using Dimensional Reduction
Order diagrams allow human analysts to understand and analyze structural properties of ordered data.
Computational Geometry Combinatorics 68R10, 06A07 G.2.2
Triadic Exploration and Exploration with Multiple Experts
In this paper we present triadic exploration based on Triadic Concept Analysis to explore conditional attribute implications in a triadic domain.
Topic Space Trajectories: A case study on machine learning literature
In this task, researchers can be supported by automated publication analysis.
Interactive Collaborative Exploration using Incomplete Contexts
However, there is up to now no theory that models the interaction of multiple experts for the task of attribute exploration with incomplete knowledge.
Orometric Methods in Bounded Metric Data
Notably, metric sets of items inclosed in knowledge graphs.
Collaborative Interactive Learning -- A clarification of terms and a differentiation from other research fields
The field of collaborative interactive learning (CIL) aims at developing and investigating the technological foundations for a new generation of smart systems that support humans in their everyday life.
DimDraw -- A novel tool for drawing concept lattices
Concept lattice drawings are an important tool to visualize complex relations in data in a simple manner to human readers.
Discovering Implicational Knowledge in Wikidata
Knowledge graphs have recently become the state-of-the-art tool for representing the diverse and complex knowledge of the world.
Relevant Attributes in Formal Contexts
Computing conceptual structures, like formal concept lattices, is in the age of massive data sets a challenging task.
Distances for WiFi Based Topological Indoor Mapping
For localization and mapping of indoor environments through WiFi signals, locations are often represented as likelihoods of the received signal strength indicator.
Intrinsic dimension and its application to association rules
This work summarizes the first attempt to provide a computationally feasible method for measuring the extent of dimension curse present in a data set with respect to a particular class machine of learning procedures.
Intrinsic Dimension of Geometric Data Sets
The present work provides a comprehensive study of the intrinsic geometry of a data set, based on Gromov's metric measure geometry and Pestov's axiomatic approach to intrinsic dimension.
Adaptive kNN using Expected Accuracy for Classification of Geo-Spatial Data
This paper proposes an adaptive kNN classifier where k is chosen dynamically for each instance (point) to be classified, such that the expected accuracy of classification is maximized.
Gender Inference using Statistical Name Characteristics in Twitter
Much attention has been given to the task of gender inference of Twitter users.
