Demo Data from SIGIR 2026 / reviewers in the wild / expert
Pierluigi Miraglia
dblp:43/5735
· 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 · 2Databases, data management, data science and information retrieval · 1Theory of computation · 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.
| Artificial intelligence
1 paper |
Knowledge representation and reasoning · 100% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Knowledge representation and reasoning
knowledge-based systems |
0.0 | 1 | 2004 | Towards a Quantitative, Platform-Independent Analysis of Knowledge Systems · KR 2004 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2004 | Towards a Quantitative, Platform-Independent Analysis of Knowledge Systems
Noah S. Friedland, Paul G. Allen, Michael Witbrock, Gavin Matthews, Nancy Salay, Pierluigi Miraglia, Jürgen Angele, Steffen Staab, David J. Israel, Vinay K. Chaudhri, Bruce W. Porter, Ken Barker 0002, Peter Clark |
KR | 6 |
| 2003 | Evaluating expert-authored rules for military reasoningabstractEliciting complex logical rules directly from logic-naive subject matter experts (SMEs) is a challenging knowledge capture task. We describe a large-scale experiment to evaluate tools designed to produce SME-authored rule bases. We assess the quality of the rule bases with respect to the: 1) performance on the addressed functional task (military course of action (COA) critiquing); and 2) intrinsic knowledge representation quality. In the course of this assessment, we note both strengths and weaknesses in the state of the art, and accordingly suggest some foci for future development in this important technology area. Mike Pool, Kenneth S. Murray, Julie Fitzgerald, Mala Mehrotra, Robert Schrag, Jim Blythe, Jihie Kim, Hans Chalupsky, Pierluigi Miraglia, Thomas A. Russ, David Schneider 0005 |
K-CAP | 9 |