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Daniel Barbará
Data Mining
Machine Learning
SIAM International Conference On Data Mining
About
Daniel Barbará has taught at George Mason University since 1997. Barbará's areas of expertise are data mining and machine learning. He served as the program chair of the SIAM International Conference on Data Mining in 2003, and he has received numerous grants from the National Science Foundation, the Army, and other federal and state institutions.
Research Performance Summary
1981-2025
Active Research Span
First Recorded Paper
The cost of data replication
Year:
1981
Citations:
16
Venue:
ACM SIGCOMM Computer Communication Review 11 (4)
Latest Recorded Paper
From Contrast to Control: Domain Conditioned Masking for Small Molecule Generation of Quaternary Ammonium Compounds
Year:
2025
Citations:
0
Venue:
Companion Proceedings of the 16th ACM International Conference on
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.
Publication Venues and Collaboration
Journal, Conference, and Book Publication Breakdown
Top Coauthors
Barbara
Barbará
Garcia-Molina
Research Impact by Period
Papers
1
Citations
0
Avg. Citations / Paper
0
H-Index
0
Papers
9
Citations
36
Avg. Citations / Paper
4
H-Index
5
Papers
15
Citations
366
Avg. Citations / Paper
24.4
H-Index
9
Papers
10
Citations
220
Avg. Citations / Paper
22
H-Index
7
Papers
18
Citations
1235
Avg. Citations / Paper
68.6
H-Index
10
Papers
44
Citations
4230
Avg. Citations / Paper
96.1
H-Index
25
Papers
32
Citations
2020
Avg. Citations / Paper
63.1
H-Index
20
Papers
27
Citations
2692
Avg. Citations / Paper
99.7
H-Index
15
Papers
30
Citations
1817
Avg. Citations / Paper
60.6
H-Index
10
Papers
4
Citations
96
Avg. Citations / Paper
24
H-Index
4
Contact and Professional Links
Detected Research Keywords
Data Mining Intrusion
Mining Intrusion Detection
Detecting Threatening Behavior
Threatening Behavior Bayesian
Behavior Bayesian Networks
Cost Comparison File
Comparison File Copies
Locality Sensitive Hashing
Distributed File Systems
Transmissions Redundant Paths