Nataša Kejžar
Biographic Data
| ID | 1591944 |
|---|---|
| NAME | Nataša Kejžar |
| GIVEN NAMES | Nataša |
| FAMILY NAME | Kejžar |
| SIGNATURE | KEJŽAR N |
| AFFILIATIONS | University of Ljubljana |
| ORCID | 0000-0003-3069-9863 |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2008 |
| LATEST PUBLICATION YEAR | 2015 |
| H-INDEX | 1 |
A weighted clustering of population pyramids for the world's countries, 1996, 2001, 2006
This paper presents clusters of the world's countries obtained by a novel weighted clustering method. The approach is based on data representations with symbolic descriptions of age-sex structures. To obtain clusters with similar descriptions, a weighted clustering method is used which is suitable for data described with discrete distributions. In contrast to the classical approach, this method allows the population of each sex to be included in …
Probabilistic Inductive Classes of Graphs
A unifying framework—probabilistic inductive classes of graphs (PICGs)—is defined by imposing a probability space on the rules and their left elements from the standard notion of inductive class of graphs. The rules can model the processes creating real-world social networks, such as spread of knowledge, dynamics of acquaintanceships or sexual contacts, and emergence of clusters. We demonstrate the characteristics of PICGs by casting some well-kn…
A weighted clustering of population pyramids for the world's countries, 1996, 2001, 2006
This paper presents clusters of the world's countries obtained by a novel weighted clustering method. The approach is based on data representations with symbolic descriptions of age-sex structures. To obtain clusters with similar descriptions, a weighted clustering method is used which is suitable for data described with discrete distributions. In contrast to the classical approach, this method allows the population of each sex to be included in …
Probabilistic Inductive Classes of Graphs
A unifying framework—probabilistic inductive classes of graphs (PICGs)—is defined by imposing a probability space on the rules and their left elements from the standard notion of inductive class of graphs. The rules can model the processes creating real-world social networks, such as spread of knowledge, dynamics of acquaintanceships or sexual contacts, and emergence of clusters. We demonstrate the characteristics of PICGs by casting some well-kn…
Probabilistic Inductive Classes of Graphs
A unifying framework—probabilistic inductive classes of graphs (PICGs)—is defined by imposing a probability space on the rules and their left elements from the standard notion of inductive class of graphs. The rules can model the processes creating real-world social networks, such as spread of knowledge, dynamics of acquaintanceships or sexual contacts, and emergence of clusters. We demonstrate the characteristics of PICGs by casting some well-kn…
A weighted clustering of population pyramids for the world's countries, 1996, 2001, 2006
This paper presents clusters of the world's countries obtained by a novel weighted clustering method. The approach is based on data representations with symbolic descriptions of age-sex structures. To obtain clusters with similar descriptions, a weighted clustering method is used which is suitable for data described with discrete distributions. In contrast to the classical approach, this method allows the population of each sex to be included in …
Artificial Intelligence (1 work) · Artificial Intelligence (1 work) · Bayesian Modeling and Causal Inference (1 work) · Class (philosophy (1 work) · Cluster (spacecraft) (1 work) · Cluster analysis (1 work) · Complex Network Analysis Techniques (1 work) · Computer Science (1 work) · Contrast (vision) (1 work) · Data mining (1 work)