Rule-based Adaptation
Rule-Based Adaptation is a methodological approach in adaptive systems that uses predefined conditional rules to dynamically modify interface or content elements in response to user interactions, distinguishing itself from other adaptation techniques by relying on explicit, human-defined logic rather than statistical or machine learning models.
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4.4K
Citations
282
Authors
133
Institutions
Publications per year
2017–2026
19
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Function-based object model towards website adaptation
Jinlin Chen, Baoyao Zhou, Shi Jin et al. · 2001 · 160 citations
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133
Politecnico di Milano
Milan, Italy
4 h-index
13 publications
188 citations
Vrije Universiteit Brussel
Brussels, Belgium
4 h-index
6 publications
170 citations
Eindhoven University of Technology
Eindhoven, The Netherlands
3 h-index
8 publications
422 citations
Technische Universität Dresden
Dresden, Germany
3 h-index
6 publications
130 citations
KU Leuven
Leuven, Belgium
3 h-index
5 publications
372 citations

Imperial College London
London, United Kingdom
3 h-index
12 publications
477 citations

Peking University
Beijing, China
3 h-index
9 publications
244 citations
The University of Texas at Dallas
Richardson, United States
3 h-index
10 publications
349 citations
1–8 of 133
TFS · 5 publications · 306 citations
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4 publications · 176 citations
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TKDE · 3 publications · 106 citations
3
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2 publications · 73 citations
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TAAS · 2 publications · 163 citations
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