An Approach for Integrating Multidimensional Database into Context-Aware Recommender System - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

An Approach for Integrating Multidimensional Database into Context-Aware Recommender System

Résumé

Recommender system (RS) suggests useful items to users. Most of existing techniques in RS focus on using a rating matrix of users and items without considering recommendation context. In this paper, we take advantage of multidimensional database to present context information in context-aware RS. Therefore, we exploit the ability of OLAP aggregate operations to estimate user ratings. We propose an approach to translate the concepts of content-based, collaborative filtering and context recommendation into OLAP aggregate operations and integrate them to rating estimation function. Furthermore, through OLAP aggregate operations, our rating estimation function tends to solve the cold-start problem in RS and the data sparsity problem in context-aware RS. We develop a context-aware tour RS with our approach. In this system, we survey related researches to identify context information and user, item information being suitable to tour RS. We evaluate the system by accuracy and performance.
Fichier principal
Vignette du fichier
978-3-662-45237-0_23_Chapter.pdf (385.14 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01405590 , version 1 (30-11-2016)

Licence

Paternité

Identifiants

Citer

Mai Nhat Vinh, Nguyen Nhat Duy, Ho Thi Hoang Vy, Le Nguyen Hoai Nam. An Approach for Integrating Multidimensional Database into Context-Aware Recommender System. 13th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Nov 2014, Ho Chi Minh City, Vietnam. pp.231-242, ⟨10.1007/978-3-662-45237-0_23⟩. ⟨hal-01405590⟩
51 Consultations
124 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More