Demo Data from EDBT 2026 / reviewers in the wild / expert
Bryan Nelson
dblp:02/4158
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1Databases, data management, data science and information retrieval · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Databases, data mining, and information retrieval
1 paper |
Data mining · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational social science and digital humanities · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data mining › predictive modeling
classification |
0.0 | 1 | 2001 | Segmentation-based modeling for advanced targeted marketing · KDD 2001 |
Computational social science and digital humanities › marketing
targeted marketing |
0.0 | 1 | 2001 | Segmentation-based modeling for advanced targeted marketing · KDD 2001 |
Methods — techniques the papers use, named apart from their topics
statistical modeling · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2004 | Experimental Results for High-Speed Jitter Measurement TechniqueabstractA BIST method to measure jitter without external references is presented. Measured data from 0.25- m BiCMOS chips show jitter resolution about 30 to 50 ps over 8 cycles of a 1 GHz input signal. The measurement technique uses the clock signal under test to control the charging of the input capacitance of an ADC. One advantage of this design is that it does not require an external jitter-free reference clock or a voltage reference. Design improvements from architectures to circuits are discussed and the method has potentials in other timing measurement applications. Karen Taylor, Bryan Nelson, Alan Chong, Mani Soma, Hosam Haggag, Jeffrey M. Huard, Jim Braatz |
ITC | 2 |
| 2001 | Segmentation-based modeling for advanced targeted marketingabstractFingerhut Business Intelligence (BI) has a long and successful history of building statistical models to predict consumer behavior. The models constructed are typically segmentation-based models in which the target audience is split into subpopulations (i.e., customer segments) and individually tailored statistical models are then developed for each segment. Such models are commonly employed in the direct-mail industry; however, segmentation is often performed on an ad-hoc basis without directly considering how segmentation affects the accuracy of the resulting segment models. Fingerhut BI approached IBM Research with the problem of how to build segmentation-based models more effectively so as to maximize predictive accuracy. The IBM Advanced Targeted Marketing-Single EventsTM (IBM ATM-SETM) solution is the result of IBM Research and Fingerhut BI directing their efforts jointly towards solving this problem. This paper presents an evaluation of ATM-SE's modeling capabilities using data from Fingerhut's catalog mailings. Chidanand Apté, Eric Bibelnieks, Ramesh Natarajan, Edwin P. D. Pednault, Fateh Tipu, Deb Campbell, Bryan Nelson |
KDD | 7 |