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John C. Kunz

dblp:63/2709 · DBLP profile ↗
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16ranked-venue papers
8as first author
0since 2021 · last 2009
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 11 · 6 first-authorArtificial intelligence and machine learning · 3 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2 · 1 first-authorHuman-computer interaction and ubiquitous computing · 2Systems, architecture and hardware · 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.

Theoretical computer science
1 paper
Algorithmic game theory and mechanism design · 100%
Human-computer interaction and pervasive computing
1 paper
Collaborative and social computing · 100%
Artificial intelligence
2 papers
Knowledge representation and reasoning · 48% Trustworthy machine learning · 40% Planning, search and constraint satisfaction · 12%
Interdisciplinary, comprehensive, and emerging computing
2 papers
Medical and health informatics · 47% Computational social science and digital humanities · 40% Bioinformatics and computational biology · 12%

Topics — the 9 heaviest of 11, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Collaborative and social computing › groupware
meeting support
0.012004
Cutting to the chase: improving meeting effectiveness by focusing on the agenda · CSCW 2004
Algorithmic game theory and mechanism design
incentive mechanism
0.012004
Cutting to the chase: improving meeting effectiveness by focusing on the agenda · CSCW 2004
Algorithmic game theory and mechanism design › mechanism design › truthful mechanism
VCG mechanism
0.012004
Cutting to the chase: improving meeting effectiveness by focusing on the agenda · CSCW 2004
Knowledge, reasoning and agents › Knowledge representation and reasoning
knowledge-based systems
0.011991
Validating knowledge systems: a scheduling example · ICRA 1991
Machine learning › Trustworthy machine learning
model validation
0.011991
Validating knowledge systems: a scheduling example · ICRA 1991
Computational social science and digital humanities › causal inference
causal modeling
0.011983
Analysis of Physiological Behavior Using a Causal Model Based on First Principles · AAAI 1983
Medical and health informatics › biomedical signal processing
physiological signal analysis
0.011983
Analysis of Physiological Behavior Using a Causal Model Based on First Principles · AAAI 1983
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
scheduling
0.011991
Validating knowledge systems: a scheduling example · ICRA 1991
Medical and health informatics
intensive care unit
0.011979
Representation of Dynamic Clinical Knowledge: Measurement Interpretation in the Intensive Care Unit · IJCAI 1979

Methods — techniques the papers use, named apart from their topics

VCG mechanism · 0.1symbolic modeling · 0.0causal models · 0.0
YearPublicationVenuePosition
2009 Advanced engineering informatics editorial
John C. Kunz, Ian F. C. Smith, Tetsuo Tomiyama
Adv. Eng. Informatics1
2008 Editorial
John C. Kunz, Tetsuo Tomiyama, Ian F. C. Smith
Adv. Eng. Informatics1
2007 Advanced Engineering Informatics
John C. Kunz, Ian F. C. Smith, Tetsuo Tomiyama
Adv. Eng. Informatics1
2006 20th Anniversary
John C. Kunz, Ian F. C. Smith, Tetsuo Tomiyama
Adv. Eng. Informatics1
2005 Obituary for Professor Rob Milne
John C. Kunz
Adv. Eng. Informatics1
2005 Editorial
Ian F. C. Smith, John C. Kunz, Tetsuo Tomiyama
Adv. Eng. Informatics2
2004 Cutting to the chase: improving meeting effectiveness by focusing on the agenda
abstract
We propose an agenda planning technique with a built-in incentive mechanism, based on the VCG (Vickrey-Clarke-Groves) method from game theory, to help project managers in the engineering construction industry create a more effective agenda. Preliminary results have shown an improvement in both instrumented and perceived meeting quality.
Ana Cristina Bicharra Garcia, John C. Kunz, Martin Fischer 0010
CSCW2
2004 Building a project ontology with extreme collaboration and virtual design and construction
Ana Cristina Bicharra Garcia, John C. Kunz, Martin Ekstrom, Arto Kiviniemi
Adv. Eng. Informatics2
2004 Perspectors: composable, reusable reasoning modules to construct an engineering view from other engineering views
John Haymaker, John C. Kunz, Ben Suter, Martin Fischer 0010
Adv. Eng. Informatics2
2003 A generic feature-driven activity-based cost estimation process
Sheryl Staub-French, Martin Fischer 0010, John C. Kunz, Boyd Paulson
Adv. Eng. Informatics3
2002 A performance-based approach to wheelchair accessible route analysis
Charles S. Han, Kincho H. Law, Jean-Claude Latombe, John C. Kunz
Adv. Eng. Informatics4
2002 Editorial
John C. Kunz, Ian F. C. Smith, Tetsuo Tomiyama
Adv. Eng. Informatics1
1998 Visualization of Construction Planning Information
abstract
A construction schedule helps planners to identity potential construction problems prior to actual building construction. Planners must envision the sequence of construction, the workspace logistics, and utilization of resources and equipment in space and over time. This paper discusses methods of generating, visuaMng, and evahrating construction planning information with CAD based tools. We use a construction example to illustrate how feature extraction of 3D CAD models can help identify construction problems and evaluate the quality of a construction plan through 4D analysis and 4D annotation.
Kathleen McKinney, John C. Kunz, Martin Fischer 0010
IUI2
1991 Validating knowledge systems: a scheduling example
abstract
The models discussed are symbolic, explicitly describing concepts, parameters, and relations among concepts and parameters. They are formal in that they represent the design of the business and its processes as described by professional decision-makers. A methodology is presented for building such model-based systems, and some of the practical issues of building and validating models are discussed.>
John C. Kunz, Nizwer Husain
ICRA1
1983 Analysis of Physiological Behavior Using a Causal Model Based on First Principles
John C. Kunz
AAAI1
1979 Representation of Dynamic Clinical Knowledge: Measurement Interpretation in the Intensive Care Unit
Lawrence M. Fagan, John C. Kunz, Edward A. Feigenbaum, John J. Osborn
IJCAI2