Dmitriy Korobskiy
Biographic Data
| ID | 9458056 |
|---|---|
| NAME | Dmitriy Korobskiy |
| GIVEN NAMES | Dmitriy |
| FAMILY NAME | Korobskiy |
| SIGNATURE | KOROBSKIY D |
| AFFILIATIONS | NETE (United States) |
| ORCID | 0000-0002-7909-0218 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Center–periphery structure in research communities
Clustering and community detection in networks are of broad interest and have been the subject of extensive research that spans several fields. We are interested in the relatively narrow question of detecting communities of scientific publications that are linked by citations. These publication communities can be used to identify scientists with shared interests who form communities of researchers. Building on the well-known k-core algorithm, we …
Finding scientific communities in citation graphs
Understanding the nature and organization of scientific communities is of broad interest. The “Invisible College” is a historical metaphor for one such type of community that refers to a small group of scientists working on a problem of common interest. The scientific and social behavior of such colleges has been the subject of case studies that have examined limited samples of the scientific enterprise. We introduce a metamethod for large-scale …
Viewing computer science through citation analysis
Frequently cocited publications
Cocitation measurements can reveal the extent to which a concept representing a novel combination of existing ideas evolves towards a specialty. The strength of cocitation is represented by its frequency, which accumulates over time. Of interest is whether underlying features associated with the strength of cocitation can be identified. We use the proximal citation network for a given pair of articles ( x, y) to compute θ, an a priori estimate of…
Co-citations in context
Citation analysis of the scientific literature has been used to study and define disciplinary boundaries, to trace the dissemination of knowledge, and to estimate impact. Co-citation, the frequency with which pairs of publications are cited, provides insight into how documents relate to each other and across fields. Co-citation analysis has been used to characterize combinations of prior work as conventional or innovative and to derive features o…
No prominent works on this page.
Viewing computer science through citation analysis
Frequently cocited publications
Cocitation measurements can reveal the extent to which a concept representing a novel combination of existing ideas evolves towards a specialty. The strength of cocitation is represented by its frequency, which accumulates over time. Of interest is whether underlying features associated with the strength of cocitation can be identified. We use the proximal citation network for a given pair of articles ( x, y) to compute θ, an a priori estimate of…
Co-citations in context
Citation analysis of the scientific literature has been used to study and define disciplinary boundaries, to trace the dissemination of knowledge, and to estimate impact. Co-citation, the frequency with which pairs of publications are cited, provides insight into how documents relate to each other and across fields. Co-citation analysis has been used to characterize combinations of prior work as conventional or innovative and to derive features o…
Finding scientific communities in citation graphs
Understanding the nature and organization of scientific communities is of broad interest. The “Invisible College” is a historical metaphor for one such type of community that refers to a small group of scientists working on a problem of common interest. The scientific and social behavior of such colleges has been the subject of case studies that have examined limited samples of the scientific enterprise. We introduce a metamethod for large-scale …
Center–periphery structure in research communities
Clustering and community detection in networks are of broad interest and have been the subject of extensive research that spans several fields. We are interested in the relatively narrow question of detecting communities of scientific publications that are linked by citations. These publication communities can be used to identify scientists with shared interests who form communities of researchers. Building on the well-known k-core algorithm, we …
Citation (4 works) · Complex Network Analysis Techniques (4 works) · scientometrics and bibliometrics research (4 works) · Artificial Intelligence (2 works) · Citation analysis (2 works) · Cluster analysis (2 works) · Computer Science (2 works) · Data science (2 works) · Library science (2 works) · Scientific literature (2 works)