Maria Rosaria D’esposito
Biographic Data
| ID | 220698 |
|---|---|
| NAME | Maria Rosaria D’esposito |
| GIVEN NAMES | Maria Rosaria |
| FAMILY NAME | D’esposito |
| SIGNATURE | D’ESPOSITO M R |
| AFFILIATIONS | University of Salerno |
| ORCID | 0000-0001-9963-8378 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 20 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2014 |
| LATEST PUBLICATION YEAR | 2015 |
| H-INDEX | 2 |
Multiple factor analysis for time-varying two-mode networks
Most social networks present complex structures. They can be both multi-modal and multi-relational. In addition, each relationship can be observed across time occasions. Relational data observed in such conditions can be organized into multidimensional arrays and statistical methods from the theory of multiway data analysis may be exploited to reveal the underlying data structure. In this paper, we adopt an exploratory data analysis point of view…
On the use of Multiple Correspondence Analysis to visually explore affiliation networks
On the use of Multiple Correspondence Analysis to visually explore affiliation networks
Multiple factor analysis for time-varying two-mode networks
Most social networks present complex structures. They can be both multi-modal and multi-relational. In addition, each relationship can be observed across time occasions. Relational data observed in such conditions can be organized into multidimensional arrays and statistical methods from the theory of multiway data analysis may be exploited to reveal the underlying data structure. In this paper, we adopt an exploratory data analysis point of view…
On the use of Multiple Correspondence Analysis to visually explore affiliation networks
Multiple factor analysis for time-varying two-mode networks
Most social networks present complex structures. They can be both multi-modal and multi-relational. In addition, each relationship can be observed across time occasions. Relational data observed in such conditions can be organized into multidimensional arrays and statistical methods from the theory of multiway data analysis may be exploited to reveal the underlying data structure. In this paper, we adopt an exploratory data analysis point of view…
Artificial Intelligence (2 works) · Complex Network Analysis Techniques (2 works) · Computer Science (2 works) · Data mining (2 works) · Data Visualization and Analytics (2 works) · Human–computer interaction (2 works) · Machine learning (2 works) · Mode (computer interface (2 works) · Network analysis (2 works) · Theoretical Computer Science (2 works)