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Lawrence S. Lefkowitz

dblp:84/1911 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning
knowledge acquisition
0.011988
Knowledge Acquisition as Knowledge Assimilation · Int. J. Man Mach. Stud. 1988
Knowledge, reasoning and agents › Knowledge representation and reasoning › knowledge management
knowledge internalization
0.011988
Knowledge Acquisition as Knowledge Assimilation · Int. J. Man Mach. Stud. 1988
Collaborative and social computing
office information systems
0.011984
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
YearPublicationVenuePosition
1988 Knowledge Acquisition as Knowledge Assimilation
Lawrence S. Lefkowitz, Victor R. Lesser
Int. J. Man Mach. Stud.1
1984 Task Support in an Office System
abstract
A 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
ICDCS4