Ray Bareiss

998 citations
36 papers · 572 · h-index 10

Impact in

Papers in

Ray Bareiss

31 papers receiving 480 citations

Peers

Ray Bareiss
Comparison fields: 5 of 79
  • Computer Science Applications 91
  • Artificial Intelligence 346
  • Developmental and Educational Psychology 101
  • Software 27
  • Information Systems 139
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Citations per field
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Citations per year

Countries citing papers authored by Ray Bareiss

Since Specialization
Citations

This map shows the geographic impact of Ray Bareiss's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ray Bareiss with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ray Bareiss more than expected).

Fields of papers citing papers by Ray Bareiss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ray Bareiss. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ray Bareiss. The network helps show where Ray Bareiss may publish in the future.

Co-authors

The 20 scholars most cited alongside Ray Bareiss, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ray Bareiss Line = papers co-authored together Ray Bareiss links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1990164
2
Exemplar-Based Knowledge Acquisition: A Unified Approach to Concept Representation, Classification, and Learning
199085
3 199278
4 199438
5 198933
6 199629
7 199326
8 200018
9 200817
10 201011
11 20118
12 20128
13 19987
14 19985
15 20085
16 19964
17 20104
18
Integrating organizational memory and performance support
19994
19
Automated index generation for constructing large-scale conversational hypermedia systems
19933
20
A memory architecture for case-based argumentation
19923

About Ray Bareiss

Ray Bareiss is a scholar working on Artificial Intelligence, Computer Science Applications, Information Systems, Developmental and Educational Psychology and Computer Vision and Pattern Recognition, having authored 36 papers that have together received 572 indexed citations. Recurring topics across this work include Software Engineering Techniques and Practices (9 papers), Teaching and Learning Programming (7 papers), Innovative Teaching and Learning Methods (5 papers), AI-based Problem Solving and Planning (4 papers), Multimedia Communication and Technology (4 papers), Intelligent Tutoring Systems and Adaptive Learning (4 papers), Video Analysis and Summarization (4 papers) and Speech and dialogue systems (3 papers). The work is most often cited by research in Computer Science Applications (91 citations), Artificial Intelligence (346 citations), Developmental and Educational Psychology (101 citations), Software (27 citations) and Information Systems (139 citations). Ray Bareiss has collaborated with scholars based in United States, Canada and Finland. Frequent co-authors include Bruce Porter, Robert C. Holte, Lawrence Birnbaum, William D. Ferguson, Richard Beckwith, Benjamin Bell, Martin Griss, Thomas R. Hinrichs, Larry Birnbaum and Christopher Johnson. Their work appears in journals such as Journal of the Learning Sciences, Machine Learning, Artificial Intelligence, SHILAP Revista de lepidopterología and ACM SIGCSE Bulletin.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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