Abstract
| Original language | English |
|---|---|
| Title of host publication | 21st International Conference on Control Systems and Computer Science (CSCS) |
| Publisher | IEEE |
| ISBN (Electronic) | 2379-0482 |
| DOIs | |
| Publication status | Published - 7 Jul 2017 |
| Externally published | Yes |
| Event | 21st Int. Conf. on Control Systems and Computer Science (CSCS21) - Bucharest, Romania Duration: 29 May 2017 → 31 May 2017 https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7963998 https://cscs21.hpc.pub.ro/ |
Conference
| Conference | 21st Int. Conf. on Control Systems and Computer Science (CSCS21) |
|---|---|
| Abbreviated title | CSCS21 |
| Country | Romania |
| City | Bucharest |
| Period | 29/05/17 → 31/05/17 |
| Internet address |
Fingerprint
Keywords
- semantic similarity
- discourse analysis
- co-authorship networks
- social network analysis
Cite this
}
Semantic Similarity versus Co-authorship Networks: A Detailed Comparison. / Paraschiv, Ionut Cristian; Dascalu, Mihai; Trausan-Matu, Stefan; Nistor, Nicolae; Montes de Oca, Ambar Murillo; McNamara, Danielle S.
21st International Conference on Control Systems and Computer Science (CSCS). IEEE, 2017.Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review
TY - GEN
T1 - Semantic Similarity versus Co-authorship Networks: A Detailed Comparison
AU - Paraschiv, Ionut Cristian
AU - Dascalu, Mihai
AU - Trausan-Matu, Stefan
AU - Nistor, Nicolae
AU - Montes de Oca, Ambar Murillo
AU - McNamara, Danielle S.
PY - 2017/7/7
Y1 - 2017/7/7
N2 - Whether interested in personal work, in learning about trending topics, or in finding the structure of a specific domain, individuals' work of staying up-to-date has become more and more difficult due to the increasing information overflow. ln our previous work our focus has been to create a semantic annotation model accompanied by dedicated views to explore the semantic similarities between scientific articles. This paper focuses on applying our approach on a dataset of 519 project proposal abstracts, with the intention to bring value to the current indexation methodologies that rely primarily on co- citations and keyword matching. Our experiment uses various Social Network Analysis metrics to compare the rankings generated by two complementary models relying on semantic similarity and co-authorship networks. The two models are statistically different based on representative project associations, are significantly correlated in terms of project rankings by eccentricity and closeness centrality, and the semantic similarity network is denser.
AB - Whether interested in personal work, in learning about trending topics, or in finding the structure of a specific domain, individuals' work of staying up-to-date has become more and more difficult due to the increasing information overflow. ln our previous work our focus has been to create a semantic annotation model accompanied by dedicated views to explore the semantic similarities between scientific articles. This paper focuses on applying our approach on a dataset of 519 project proposal abstracts, with the intention to bring value to the current indexation methodologies that rely primarily on co- citations and keyword matching. Our experiment uses various Social Network Analysis metrics to compare the rankings generated by two complementary models relying on semantic similarity and co-authorship networks. The two models are statistically different based on representative project associations, are significantly correlated in terms of project rankings by eccentricity and closeness centrality, and the semantic similarity network is denser.
KW - semantic similarity
KW - discourse analysis
KW - co-authorship networks
KW - social network analysis
U2 - 10.1109/CSCS.2017.86
DO - 10.1109/CSCS.2017.86
M3 - Conference article in proceeding
BT - 21st International Conference on Control Systems and Computer Science (CSCS)
PB - IEEE
ER -