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Istituto di scienza dell'alimentazione

Torna all'elenco Contributi in rivista anno 2010

Contributo in rivista

Tipo: Articolo in rivista

Titolo: A multimedia recommender integrating object features and user behavior

Anno di pubblicazione: 2010

Formato: Cartaceo

Autori: M. Albanese; A. Chianese; A. d’Acierno; V. Moscato; A. Picariello

Affiliazioni autori: M. Albanese - UMIACS, University of Maryland, College Park, MD 20742, USA A. Chianese, V. Moscato, A. Picariello - DIS, University of Naples "Federico II", Via Claudio, 21, 80125 Naples, Italy A. d'Acierno - ISA, CNR, Via Roma 64, Avellino 83100, Italy

Autori CNR:

  • ANTONIO D'ACIERNO

Lingua: inglese

Abstract: Despite the great amount of work done in the last decade, retrieving information of interest from a large multimedia repository still remains an open issue. In this paper, we propose an intelligent browsing system based on a novel recommendation paradigm. Our approach combines usage patters with low-level features and semantic descriptors in order to predict users' behavior and provide effective recommendations. The proposed paradigm is very general and can be applied to any type of multimedia data. In order to make the recommender system even more flexible, we introduce the concept of multichannel browser, i.e. a browser that allows concurrent browsing of multiple media channels. We implemented a prototype of the proposed system and tested the effectiveness of our approach in a virtual museum scenario. Experimental results have proved that the system greatly enhances users' experience, thus encouraging further research in this direction.

Lingua abstract: inglese

Pagine da: 563

Pagine a: 585

Pagine totali: 22

Rivista:

Multimedia tools and applications Kluwer Academic Publishers
Paese di pubblicazione: Stati Uniti d'America
Lingua: inglese
ISSN: 1380-7501

Numero volume: 50

DOI: 10.1007/s11042-010-0480-8

Referee: Ś: Internazionale

Indicizzato da:

  • ISI Web of Science (WOS) [000280248100007]
  • Scopus [: 2-s2.0-77955170909]

Parole chiave:

  • Recommender systems
  • Browsing
  • Information retrieval
  • Multimedia databases

URL: http://www.springerlink.com/content/50417474m3683878/

Strutture CNR:

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