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A multimedia recommender integrating object features and user behavior

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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.

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Notes

  1. Here we do not consider link-based systems mainly used in WEB search engines.

  2. Ad-hoc metrics could be defined to evaluate the similarity of non-taxonomic attributes. Without loss of generality, we omit further discussions on this topic.

  3. We will discuss in Section 6.2 how to build this set.

  4. We use cookies to track sessions, and don’t set an expiration date, so they will be deleted when the browser session ends. In this way, different users browsing the collection from a shared computer (e.g., in a public library) will not misinterpreted as the same user.

  5. The people involved in the experiments were mainly students from the University of Naples, Italy.

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Authors and Affiliations

  1. UMIACS, University of Maryland, College Park, MD, 20742, USA

    Massimiliano Albanese

  2. DIS, University of Naples “Federico II”, Via Claudio, 21, 80125, Naples, Italy

    Angelo Chianese, Vincenzo Moscato & Antonio Picariello

  3. ISA, CNR, Via Roma 64, Avellino, 83100, Italy

    Antonio d’Acierno

Authors
  1. Massimiliano Albanese
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  2. Angelo Chianese
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  3. Antonio d’Acierno
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  4. Vincenzo Moscato
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  5. Antonio Picariello
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Correspondence to Massimiliano Albanese.

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Albanese, M., Chianese, A., d’Acierno, A. et al. A multimedia recommender integrating object features and user behavior. Multimed Tools Appl 50, 563–585 (2010). https://doi.org/10.1007/s11042-010-0480-8

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