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        Information Sciences (Elsevier) Special Issue on:

                        *Multimedia Modeling*

*Guest Editors*
     * Meng Wang, Hefei University of Technology, China
     * Dacheng Tao, University of Technology, Sydney
     * Benoit Huet, EURECOM, France

*Important Dates*
     * February 22, 2013:     Manuscript submission deadline (extended by three weeks)
     * April 1, 2013:             First-round notification
     * June 1, 2013:             Revision submission
     * August 1, 2013:         Final decision

*Information for Authors*
All manuscripts and any supplementary material should be submitted through Elsevier Editorial System (EES). The authors must select as “Multimedia Modeling” when they reach the “Article Type” step in the submission process. The EES website is located at: http://www.ees.elsevier.com/ins.

The effective and efficient modeling of multimedia data has attracted extensive research interests over last decades. Nowadays, multimedia modeling forms the basis of a wide variety of applications and services, such as search, recommendation, advertising, and personalization. But multimedia data are growing in an explosive way, and such scale brings significant challenges and profound impacts to multimedia modeling in different aspects. For example, it is very challenging for many classification, clustering and labeling algorithms to effectively and efficiently handle large-scale multimedia data, especially when the scale comes up from tens of thousands to tens of millions or even billions. Feature extraction process also needs to speed up. Fortunately, along with the growth of multimedia data, more and more resources also become available, such as the associated metadata, context and social information. In addition, collaborative tagging, a representative behavior of web 2.0, enables the availability of tags for a large amount of multimedia signals on the Internet. These facts have provided opportunities to tackle the difficulties in multimedia modeling. Recently, many research efforts are dedicated to developing new technologies for the modeling of multimedia data. There is a trend that the data scales in the research communities are shifting from thousands to hundreds of thousands, millions, and even billions. This special issue is intended to bring together the greatest research efforts in this direction and introduce them to readers. The goals of this special issue will be threefold: (1) introducing novel research work and systems on multimedia modeling; (2) surveying the progress of this area in the past years; (3) discussing new technologies that will be potentially impactful, especially those with heavily creative commentary, evaluation and suggestion.

The topics of this special issue include, but are not limited to:

•       Multimedia feature extraction, including global and local feature extraction, keypoint detection, visual vocabulary construction, feature selection, etc.
•       Multimedia modeling methods, including classification, regression, clustering, ranking, etc.
•       Multimedia tagging, including image/video/audio tagging, tag recommendation, tag refinement, tag enrichment, etc.
•       Feature-level indexing, including hashing, inverted file indexing, visual dictionary construction and refinement, etc.
•       Large-scale multimedia duplicate/near-duplication/copy detection and localization.
•       Multimedia representation, including feature extraction, distance learning, similarity learning, kernel learning, etc.
•       Techniques for speeding up multimedia classification, ranking, re-ranking, presentation, etc.
•       Applications of multimedia modeling, including search, summarization, browsing, management, sharing, advertising, etc.
•       Benchmark for research on multimedia modeling.

Please address all correspondences regarding this special issue to the Guest Editors Dr. Meng Wang ([log in to unmask]), Dr.Dacheng Tao ([log in to unmask]), and Dr. Benoit Huet ([log in to unmask]).

Best regards,

Meng, Dacheng, Benoit

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