A Personalized Recommendation Framework based on CAM and Document Annotations

被引：9

作者：

Broisin, Julien ^{[1
]}

Brut, Mihaela ^{[1
]}

Butoianu, Valentin ^{[1
]}

Sedes, Florence ^{[1
]}

Vidal, Philippe ^{[1
]}

机构：

[1] Univ Toulouse 3, Inst Rech Informat Toulouse, F-31062 Toulouse 4, France

来源：

PROCEEDINGS OF THE 1ST WORKSHOP ON RECOMMENDER SYSTEMS FOR TECHNOLOGY ENHANCED LEARNING (RECSYSTEL 2010) | 2010年 / 1卷 / 02期

关键词：

Personalized recommendation; attention metadata; semantic web; annotation-based algorithm; ontology-based modeling;

D O I：

10.1016/j.procs.2010.08.009

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a solution for recommending documents to students according to their current activity that is tracked in terms of semantic annotations associated to the accessed resources. Our approach is based on an existing tracking system that captures the user current activity, which is extended to build a user profile that comprises his/her interests in term of ontological concepts. A recommendation service is elaborated, implementing an algorithm that is alimented by Contextualized Attention Metadata (CAM) comprising the annotation of documents accessed by learners. The user profile is updated as soon as an activity is completed; thus, recommendations provided by the service are up-to-date in real time. The original aspect of this recommendation approach consists in combining a user activity tracking system with the exploitation of the semantic annotations associated with resources. (C) 2010 Published by Elsevier B.V.

引用

页码：2839 / 2848

页数：10

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