K
Kilian Stoffel
Researcher at University of Neuchâtel
Publications - 70
Citations - 1429
Kilian Stoffel is an academic researcher from University of Neuchâtel. The author has contributed to research in topics: Ontology (information science) & Temporal logic. The author has an hindex of 16, co-authored 70 publications receiving 1284 citations. Previous affiliations of Kilian Stoffel include University of Fribourg & University of Maryland, College Park.
Papers
More filters
Journal ArticleDOI
Theoretical Comparison between the Gini Index and Information Gain Criteria
TL;DR: A formal methodology is introduced, which allows us to compare multiple split criteria and permits us to present fundamental insights into the decision process.
Book ChapterDOI
Parallel k/h-Means Clustering for Large Data Sets
TL;DR: The realization of a parallel version of the k/h-means clustering algorithm is described and it is shown how a database can be distributed and how the algorithm can be applied to this distributed database.
Proceedings Article
Efficient management of very large ontologies
TL;DR: The architecture of the system uses the secondary storage of a relational data base system, efficient memory management, and parallelism to answer complex queries in very large ontologies in a few seconds on a single processor machine and in fractions of a second on parallel super computers.
Journal ArticleDOI
Simulation modelling of ecological hierarchies in constructive dynamical systems
TL;DR: It turns out that a multi-modelling approach linking all these formalisms and oriented toward the specification of a constructive dynamical system would be able to express the dynamical structure of the hierarchy and the functional and structural links between levels of organization.
Ontology-based Induction of High Level Classification Rules.
TL;DR: An algorithm based on the query facilities provided by ParkaDB, a knowledge representation system, is described, which extends the range of queries that can be issued against databases and develops a classi cati on algorithm that will nd classi cats on rules at multiple levels of abstraction.