Demo Data from SIGIR 2026 / reviewers in the wild / expert
Stephen Lee Hansen
dblp:90/4228
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2003
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 first-author
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.
| Network and information security
1 paper |
Privacy and data protection · 100% | |
| Theoretical computer science
1 paper |
Graph algorithms and graph theory · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Privacy and data protection
anonymization |
0.0 | 1 | 2003 | A Polynomial Algorithm for Optimal Univariate Microaggregation · IEEE Trans. Knowl. Data Eng. 2003 |
Privacy and data protection › anonymization › microdata anonymization
microaggregation |
0.0 | 1 | 2003 | A Polynomial Algorithm for Optimal Univariate Microaggregation · IEEE Trans. Knowl. Data Eng. 2003 |
Graph algorithms and graph theory
graph algorithms |
0.0 | 1 | 2003 | A Polynomial Algorithm for Optimal Univariate Microaggregation · IEEE Trans. Knowl. Data Eng. 2003 |
Graph algorithms and graph theory
shortest path |
0.0 | 1 | 2003 | A Polynomial Algorithm for Optimal Univariate Microaggregation · IEEE Trans. Knowl. Data Eng. 2003 |
Methods — techniques the papers use, named apart from their topics
polynomial algorithm · 0.1network flow · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | A Polynomial Algorithm for Optimal Univariate MicroaggregationabstractMicroaggregation is a technique used by statistical agencies to limit disclosure of sensitive microdata. Noting that no polynomial algorithms are known to microaggregate optimally, Domingo-Ferrer and Mateo-Sanz have presented heuristic microaggregation methods. This paper is the first to present an efficient polynomial algorithm for optimal univariate microaggregation. Optimal partitions are shown to correspond to shortest paths in a network. Stephen Lee Hansen, Sumitra Mukherjee |
IEEE Trans. Knowl. Data Eng. | 1 |