D-Index & Metrics Best Publications

David Traum

University of Southern California
United States

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 56 Citations 12,612 292 World Ranking 2694 National Ranking 1436

Overview

What is he best known for?

The fields of study David Traum is best known for:

Thermodynamics
Computer graphics (images)
Politics

His study on Visual arts is interrelated to topics such as Realism and Entertainment. His research brings together the fields of Visual arts and Realism. He integrates Entertainment with Politics in his study. In his work, David Traum performs multidisciplinary research in Politics and Representation (politics). David Traum connects relevant research areas such as Arabic and Proxemics in the domain of Linguistics. He conducted interdisciplinary study in his works that combined Human–computer interaction and Computer graphics (images). In his works, David Traum performs multidisciplinary study on Computer graphics (images) and Human–computer interaction. As part of his studies on Law, he often connects relevant subjects like Negotiation. His Law research extends to the thematically linked field of Negotiation.

His most cited work include:

Sharing Solutions: Persistence and Grounding in Multimodal Collaborative Problem Solving (218 citations)
Multi-party, Multi-issue, Multi-strategy Negotiation for Multi-modal Virtual Agents (122 citations)
All Together Now (122 citations)

What are the main themes of his work throughout his whole career to date

His research on Human–computer interaction frequently links to adjacent areas such as Virtual agent. He undertakes interdisciplinary study in the fields of Artificial intelligence and Embodied cognition through his research. In his papers, he integrates diverse fields, such as Natural language processing and Linguistics. David Traum undertakes interdisciplinary study in the fields of Linguistics and Natural language processing through his research. Many of his studies on Law apply to Negotiation as well. His Negotiation study frequently draws connections to adjacent fields such as Law. His studies link Virtual actor with Virtual reality. His Virtual actor study frequently links to adjacent areas such as Virtual reality. David Traum integrates World Wide Web and Multimedia in his research.

David Traum most often published in these fields:

Human–computer interaction (63.64%)
Artificial intelligence (51.52%)
Natural language processing (36.36%)

What were the highlights of his more recent work (between 2014-2020)?

Mathematical analysis (66.67%)
Natural language processing (66.67%)
Artificial intelligence (66.67%)

In recent works David Traum was focusing on the following fields of study:

Many of his studies involve connections with topics such as Scheme (mathematics) and Domain (mathematical analysis) and Mathematical analysis. David Traum conducts interdisciplinary study in the fields of Domain (mathematical analysis) and Mathematical analysis through his research. David Traum connects Natural language processing with Information retrieval in his study. While working on this project, David Traum studies both Information retrieval and Artificial intelligence. His research on Artificial intelligence often connects related areas such as Annotation. He undertakes interdisciplinary study in the fields of Annotation and Natural language processing through his research. Many of his studies involve connections with topics such as Virtual agent and Human–computer interaction. His research on Virtual agent frequently links to adjacent areas such as Human–computer interaction. His research on Certainty frequently connects to adjacent areas such as Geometry.

Between 2014 and 2020, his most popular works were:

Overview of the Ninth Dialog System Technology Challenge: DSTC9 (25 citations)
Dialogue Act Annotation with the ISO 24617-2 Standard (20 citations)
SimSensei Demonstration: A Perceptive Virtual Human Interviewer for Healthcare Applications (16 citations)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Information state and dialogue management in the TRINDI dialogue move engine toolkit

Staffan Larsson;David R. Traum.
Natural Language Engineering (2000)

647 Citations

A Computational Theory of Grounding in Natural Language Conversation

David Rood Traum.
(1994)

590 Citations

The role of grounding in collaborative learning tasks

Michael Baker;Tia Hansen;Richard Joiner;David Traum.
Collaborative Learning : Cognitive and Computational Approaches. (1999)

517 Citations

The Information State Approach to Dialogue Management

David R. Traum;Staffan Larsson.
(2003)

435 Citations

The TRAINS Project: A Case Study in Defining a Conversational Planning Agent

James F. Allen;Lenhart K. Schubert;George Ferguson;Peter Heeman.
Journal of Experimental and Theoretical Artificial Intelligence (1994)

422 Citations

SimSensei kiosk: a virtual human interviewer for healthcare decision support

David DeVault;Ron Artstein;Grace Benn;Teresa Dey.
adaptive agents and multi-agents systems (2014)

414 Citations

Conversation Acts in Task-Oriented Spoken Dialogue

David R. Traum;Elizabeth A. Hinkelman.
computational intelligence (1992)

371 Citations

Embodied agents for multi-party dialogue in immersive virtual worlds

David Traum;Jeff Rickel.
adaptive agents and multi-agents systems (2002)

331 Citations

Sharing Solutions: Persistence and Grounding in Multimodal Collaborative Problem Solving

Pierre Dillenbourg;David Traum.
The Journal of the Learning Sciences (2006)

322 Citations

Discourse Obligations in Dialogue Processing

David R. Traum;James F. Allen.
meeting of the association for computational linguistics (1994)

321 Citations

If you think any of the details on this page are incorrect, let us know.