Knowledge-driven profile dynamics

被引：0
|
作者：
Ferme, Eduardo [1 ,2 ]
Garapa, Marco [1 ,3 ]
Reis, Mauricio D. L. [1 ,3 ]
Almeida, Yuri [1 ,2 ]
Paulino, Teresa [1 ,2 ,4 ]
Rodrigues, Mariana [1 ]
机构：
[1] Univ Madeira, Campus Univ Penteada, P-9020105 Funchal, Portugal
[2] NOVA Lab Comp Sci & Informat NOVA LINCS, Costa Da Caparica, Portugal
[3] Ctr Invest & Desenvolvimento Matemat & Aplicacoes, P-3810193 Aveiro, Portugal
[4] Agencia Reg Desenvolvimento Invest Tecnol & Inovac, Funchal, Portugal
来源：
ARTIFICIAL INTELLIGENCE | 2024年 / 331卷
关键词：
Profile dynamics; Personalized systems; Belief revision; KM-update; MOBILE RECOMMENDER SYSTEM; OF-THE-ART; USER PROFILE; REVISION; FEATURES; WEB;
D O I：
10.1016/j.artint.2024.104117
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In the last decades, user profiles have been used in several areas of information technology. In the literature, most research works, and systems focus on the creation of profiles (using Data Mining techniques based on user's navigation or interaction history). In general, the dynamics of profiles are made by means of a systematic recreation of the profiles, without using the previous profiles. In this paper we propose to formalize the creation, representation, and dynamics of profiles from a Knowledge-Driven perspective. We introduce and axiomatically characterize four operators for changing profiles using a belief change inspired approach.
引用
收藏
页数：30
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