Demo Data from EDBT 2026 / reviewers in the wild / expert
Lawrence S. Lefkowitz
dblp:84/1911
· DBLP profile ↗
3ranked-venue papers
1as first author
0since 2021 · last 1988
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1Databases, data management, data science and information retrieval · 1Human-computer interaction and ubiquitous computing · 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.
| Artificial intelligence
1 paper |
Knowledge representation and reasoning · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
User interface design and tools · 77% Collaborative and social computing · 23% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Knowledge representation and reasoning
knowledge acquisition |
0.0 | 1 | 1988 | Knowledge Acquisition as Knowledge Assimilation · Int. J. Man Mach. Stud. 1988 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › knowledge management
knowledge internalization |
0.0 | 1 | 1988 | Knowledge Acquisition as Knowledge Assimilation · Int. J. Man Mach. Stud. 1988 |
Collaborative and social computing
office information systems |
0.0 | 1 | 1984 | Task Support in an Office System · ACM Trans. Inf. Syst. 1984 |
Methods — techniques the papers use, named apart from their topics
procedure-based representation · 0.0goal-based representation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1988 | Knowledge Acquisition as Knowledge Assimilation
Lawrence S. Lefkowitz, Victor R. Lesser |
Int. J. Man Mach. Stud. | 1 |
| 1984 | Task Support in an Office SystemabstractA major goal of an office system is to support tasks that are central to office functions.Some office tasks are readily implemented with generic office tools, such as calendars, forms packages, and mail.Many tasks, however, involve complex sequences of actions which do not all correspond to tool invocations but, instead, rely on the problem-solving abilities of office workers.In this paper we describe a system (POISE) than can be used to both automate routine tasks and provide assistance in more complex situations.The type of assistance provided can range from maintaining a record of the tasks currently being executed to suggesting possible next steps and answering natural language queries about the tasks.The POISE system uses both a procedure-based and a goal-based representation of the tasks to achieve efficiency and flexibility.The mechanisms used by POISE are described with example procedures from a university office. W. Bruce Croft, Lawrence S. Lefkowitz |
ACM Trans. Inf. Syst. | 2 |
| 1982 | A High-Level simulation Testbed for cooperative distributed problem solving
Victor R. Lesser, Daniel D. Corkill, Jasmina Pavlin, Lawrence S. Lefkowitz, Eva Hudlicka, R. Brooks, S. Reed |
ICDCS | 4 |