Demo Data from EDBT 2026 / reviewers in the wild / expert
Katherine A. Morris
dblp:94/4878
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 1988
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 first-authorDatabases, data management, data science and information retrieval · 1 · 1 first-authorTheory of computation · 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.
| Databases, data mining, and information retrieval
1 paper |
Data models and query languages · 100% | |
| Theoretical computer science
1 paper |
Logic in computer science · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data models and query languages › datalog
datalog query optimization |
0.0 | 1 | 1988 | An Algorithm for Ordering Subgoals in NAIL! · PODS 1988 |
Data models and query languages › datalog › datalog query optimization
subgoal ordering |
0.0 | 1 | 1988 | An Algorithm for Ordering Subgoals in NAIL! · PODS 1988 |
Methods — techniques the papers use, named apart from their topics
polynomial-time algorithm · 0.0capture rules · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1988 | An Algorithm for Ordering Subgoals in NAIL!abstractRule-goal graphs are the central data structures used in the NAIL′ system, a knowledge-base system being developed at Stanford University They are constructed while testing the applicability of capture rules, and traversed while generating ICODE to evaluate queries. Generating rule-goal graphs may be reduced to the problem of ordering subgoals. This paper gives an algorithm for generating rule-goal graphs efficiently, in time polynomial in the size of the rules if the arity of recursive predicates is bounded. The graphs generated may be suboptimal for some purposes, but the algorithm will always find a rule-goal graph if one exists. The algorithm has been implemented in Cprolog, and is currently being used to generate rule-goal graphs for the NAIL′ system Katherine A. Morris |
PODS | 1 |
| 1986 | Design Overview of the NAIL! System
Katherine A. Morris, Jeffrey D. Ullman, Allen Van Gelder |
ICLP | 1 |