Abstract
Personalized Information System (PIS) aims to provide tailored services to users in various contexts. The aim of such system is to help users find relevant content easier and faster. To achieve such behavior, the system needs a user model providing information about users, e.g., about their interests, skills, background and custom information while ensuring their adaptation to the needs and preferences of each user. This system is able to learn about the preferences of individual users and to tailor the content, interface, and behavior to the user preferences. In fact, the diversity of contexts and the proliferation of profiles make personalization a very sophisticated process. Personalization is a major challenge for the information system. In fact, its quality and its adaptation to the user's preferences represent a key of success of these systems. In this context, this paper presents a personalized method based on the principle of genetic programming by extracting the best adaptation rules. © 2013 The Authors.
Recommended Citation
M. Soui et al., "Improving Adaptation Rules Quality using Genetic Programming," Procedia Computer Science, vol. 21, pp. 274 - 281, Elsevier, Jan 2013.
The definitive version is available at https://doi.org/10.1016/j.procs.2013.09.036
Department(s)
Computer Science
Publication Status
Open Access
Keywords and Phrases
Adaptation Rules; Context of Use; Genetic Programming; Personalization; Personalized Systems
International Standard Serial Number (ISSN)
1877-0509
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2024 Elsevier, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Publication Date
01 Jan 2013
