Mark Levene

23 papers receiving 420 citations

Peers

Mark Levene
Comparison fields: 5 of 112
  • Complementary and Manual Therapy 52
  • Information Systems 151
  • Computer Science Applications 35
  • Artificial Intelligence 184
  • Signal Processing 54
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Thi Ngoc Trang Tran Austria
Florence Sèdes France
Ziming Zhuang United States
Siddharth Kaza United States
Xiangwu Meng China
Attila Kiss Hungary
Ernesto Diaz-Aviles Germany
Simon Dooms Belgium
Ramjeevan Singh Thakur India
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Citations per year

Countries citing papers authored by Mark Levene

Since Specialization
Citations

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

Fields of papers citing papers by Mark Levene

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Mark Levene, 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 Mark Levene Line = papers co-authored together Mark Levene links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010226
2 199973
3 200226
4 200622
5 200820
6 200116
7 201215
8
Personalisation and Trails in Self e-Learning Networks
200413
9
An investigation of the use of simulations and video gaming for supporting exploratory learning and developing higher-order cognitive skills.
200412
10 20079
11 20086
12 20094
13 19964
14 19913
15
Personalised trails and learner profiling within e-Learning environments
20043
16 20072
17
A Suffix Tree Approach to Text Categorisation Applied to Spam Filtering
20052
18
Can navigational assistance improve search experience
20012
19
Collaborative trails and group profiling within an e-Learning environment
20042
20 20102

About Mark Levene

Mark Levene is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Developmental and Educational Psychology and Signal Processing, having authored 25 papers that have together received 466 indexed citations. Recurring topics across this work include Data Management and Algorithms (3 papers), Innovative Teaching and Learning Methods (3 papers), Open Education and E-Learning (3 papers), Semantic Web and Ontologies (2 papers), Usability and User Interface Design (2 papers), Educational Games and Gamification (2 papers), Mobile Learning in Education (2 papers) and Advanced Database Systems and Queries (2 papers). The work is most often cited by research in Complementary and Manual Therapy (52 citations), Information Systems (151 citations), Computer Science Applications (35 citations), Artificial Intelligence (184 citations) and Signal Processing (54 citations). Mark Levene has collaborated with scholars based in United Kingdom, Kenya and Hong Kong. Frequent co-authors include George Loizou, Caroline Shulman, Susan Beckerleg, Ruth J. Prince, P. Wenzel Geißler, Niki Trigoni, Wilfred Ng, Peter T. Wood, Dell Zhang and Ian M. Morison. Their work appears in journals such as The Computer Journal, Acta Informatica, Social Science & Medicine, Autonomous Agents and Multi-Agent Systems and Knowledge and Information Systems.

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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