D. Sleeman

478 total citations
14 papers, 299 citations indexed

About

D. Sleeman is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, D. Sleeman has authored 14 papers receiving a total of 299 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 2 papers in Computer Networks and Communications and 2 papers in Information Systems. Recurrent topics in D. Sleeman's work include Intelligent Tutoring Systems and Adaptive Learning (8 papers), Semantic Web and Ontologies (3 papers) and Innovative Teaching and Learning Methods (2 papers). D. Sleeman is often cited by papers focused on Intelligent Tutoring Systems and Adaptive Learning (8 papers), Semantic Web and Ontologies (3 papers) and Innovative Teaching and Learning Methods (2 papers). D. Sleeman collaborates with scholars based in United States and United Kingdom. D. Sleeman's co-authors include Ralph T. Putnam, Juliet A. Baxter, James L. Moore, Robert Ward, Anthony Kelly, John Seely Brown, Joi L. Moore, Kurt Konolige, N. S. Sridharan and Elaine Rich and has published in prestigious journals such as Cognitive Science, Lecture notes in computer science and Journal of Educational Computing Research.

In The Last Decade

D. Sleeman

14 papers receiving 259 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
D. Sleeman United States	8	182	114	96	56	49	14	299
Jonathan Sewall United States	8	303 1.7×	194 1.7×	221 2.3×	51 0.9×	50 1.0×	17	402
Michael A. Sao Pedro United States	9	169 0.9×	171 1.5×	149 1.6×	46 0.8×	67 1.4×	13	283
Masaki Uto Japan	11	183 1.0×	59 0.5×	29 0.3×	78 1.4×	64 1.3×	31	315
Alberto Piatti Switzerland	7	48 0.3×	148 1.3×	59 0.6×	34 0.6×	36 0.7×	15	219
S. Hunka Canada	4	131 0.7×	33 0.3×	80 0.8×	47 0.8×	56 1.1×	13	317
Roya Hosseini United States	11	125 0.7×	265 2.3×	146 1.5×	78 1.4×	56 1.1×	19	332
Samiha Marwan United States	11	128 0.7×	280 2.5×	147 1.5×	84 1.5×	29 0.6×	26	370
Lynn Lambert United States	8	181 1.0×	114 1.0×	43 0.4×	43 0.8×	23 0.5×	18	317
V. G. Renumol India	11	123 0.7×	211 1.9×	113 1.2×	134 2.4×	60 1.2×	21	362
Harry Kornilakis Greece	6	183 1.0×	219 1.9×	243 2.5×	111 2.0×	87 1.8×	7	400

Countries citing papers authored by D. Sleeman

Since Specialization

Citations

This map shows the geographic impact of D. Sleeman'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 D. Sleeman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Sleeman more than expected).

Fields of papers citing papers by D. Sleeman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. Sleeman. 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 D. Sleeman. The network helps show where D. Sleeman may publish in the future.

Co-authorship network of co-authors of D. Sleeman

This figure shows the co-authorship network connecting the top 25 collaborators of D. Sleeman. A scholar is included among the top collaborators of D. Sleeman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with D. Sleeman. D. Sleeman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

1.

Sleeman, D. & John Seely Brown. (2012). Intelligent Tutoring Systems. Lecture notes in computer science. 12 indexed citations

2.

Sleeman, D. & Mark A. Musen. (2008). Symbiotic relationships between semantic web and knowledge engineering : Papers from the AAAI Spring Symposium. 1 indexed citations

3.

Schorlemmer, Marco, Stephen Potter, David Robertson, & D. Sleeman. (2002). Knowledge Life-Cycle Management over a Distributed Architecture. 5(3). 2–19. 2 indexed citations

4.

Sleeman, D., Stephen Potter, David Robertson, & Marco Schorlemmer. (2002). Proceedings of the Workshop on Knowledge Transformation for the Semantic Web KTSW 2002. 1 indexed citations

5.

Sleeman, D., et al.. (1989). Studies of Diagnosis and Remediation with High School Algebra Students. Cognitive Science. 13(4). 551–568. 67 indexed citations

6.

Sleeman, D.. (1989). Studies of diagnosis and remediation with high school algebra students. Cognitive Science. 13(4). 551–568. 9 indexed citations

7.

Moore, Joi L. & D. Sleeman. (1988). Enhancing PIXIE's tutoring capabilities. International Journal of Man-Machine Studies. 28(6). 605–623. 7 indexed citations

8.

Sleeman, D.. (1987). Some challenges for intelligent tutoring systems. International Joint Conference on Artificial Intelligence. 1166–1168. 6 indexed citations

9.

Sleeman, D.. (1987). Pixie: a shell for developing intelligent tutoring systems. 239–263. 34 indexed citations

10.

Putnam, Ralph T., et al.. (1986). A Summary of Misconceptions of High School Basic Programmers. Journal of Educational Computing Research. 2(4). 459–472. 73 indexed citations

11.

Sleeman, D.. (1985). UMFE: A user modelling front-end subsystem. International Journal of Man-Machine Studies. 23(1). 71–88. 62 indexed citations

12.

Sleeman, D., et al.. (1985). User modelling panel. 1298–1302. 9 indexed citations

13.

Sleeman, D.. (1984). Intelligent Tutoring Systems: A Review.. 7 indexed citations

14.

Sleeman, D.. (1982). Inferring (Mal) Rules from Pupil's Protocols.. European Conference on Artificial Intelligence. 160–164. 9 indexed citations

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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