A Ranking Method for Multimedia Recommenders (Contributo in atti di convegno)

Type

• Prodotto della ricerca (Classe)
• Contributo in atti di convegno (Classe)

Label

• A Ranking Method for Multimedia Recommenders (Contributo in atti di convegno) (literal)

Anno

• 2010-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

• 10.1145/1816041.1816087 (literal)

Alternative label

• M. Albanese; A. d’'Acierno; V. Moscato; F. Persia; A. Picariello (2010)
  A Ranking Method for Multimedia Recommenders
  in ACM International Conference on Image and Video Retrieval (CIVR'10)
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• M. Albanese; A. d’'Acierno; V. Moscato; F. Persia; A. Picariello (literal)

Note

• Google Scholar (literal)
• Scopu (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• Massimiliano Albanese, University of Maryland, College Park, MD Antonio d'Acierno, ISA-CNR, Avellino, Italy Vincenzo Moscato, University of Naples, Napoli, Italy Fabio Persia, University of Naples, Napoli, Italy Antonio Picariello, University of Naples, Napoli, Italy (literal)

Titolo

• A Ranking Method for Multimedia Recommenders (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn

• 978-1-4503-0117-6 (literal)

Abstract

• In the last few years, recommender systems have gained sig- ni¯cant attention in the research community, due to the in- creasing availability of huge data collections, such as news archives, shopping catalogs, or virtual museums. In this scenario, there is a pressing need for applications to pro- vide users with targeted suggestions to help them navigate this ocean of information. However, no much e®ort has yet been devoted to recommenders in the ¯eld of multimedia databases. In this paper, we propose a novel approach to rec- ommendation in multimedia browsing systems, based on an importance ranking method that strongly resembles the well known PageRank ranking system. We model recommenda- tion as a social choice problem, and propose a method that computes customized recommendations by originally comb- ing intrinsic features of multimedia objects, past behavior of individual users and overall behavior of the entire commu- nity of users. We implemented a prototype of the proposed system and preliminary experiments have shown that our approach is promising. (literal)

Prodotto di

• Institute of food sciences (ISA) (Istituto)
• Sistemi per la gestione e classificazione di dati biologici (INT.P02.014.004) (Modulo)

Autore CNR

• ANTONIO D'ACIERNO (Unità di personale interno)

Incoming links:

Prodotto

• Institute of food sciences (ISA) (Istituto)
• Sistemi per la gestione e classificazione di dati biologici (INT.P02.014.004) (Modulo)

Autore CNR di

• ANTONIO D'ACIERNO (Unità di personale interno)