poster

A ranking method for multimedia recommenders

Authors:

Massimiliano Albanese,

Antonio d'Acierno,

Vincenzo Moscato,

Antonio PicarielloAuthors Info & Claims

CIVR '10: Proceedings of the ACM International Conference on Image and Video Retrieval

Pages 311 - 318

https://doi.org/10.1145/1816041.1816087

Published: 05 July 2010 Publication History

Abstract

In the last few years, recommender systems have gained significant attention in the research community, due to the increasing 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 provide users with targeted suggestions to help them navigate this ocean of information. However, no much effort has yet been devoted to recommenders in the field of multimedia databases. In this paper, we propose a novel approach to recommendation in multimedia browsing systems, based on an importance ranking method that strongly resembles the well known PageRank ranking system. We model recommendation as a social choice problem, and propose a method that computes customized recommendations by originally combing intrinsic features of multimedia objects, past behavior of individual users and overall behavior of the entire community of users. We implemented a prototype of the proposed system and preliminary experiments have shown that our approach is promising.

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Cited By

Shahbazi ZHazra DPark SByun Y(2020)Toward Improving the Prediction Accuracy of Product Recommendation System Using Extreme Gradient Boosting and Encoding ApproachesSymmetry10.3390/sym1209156612:9(1566)Online publication date: 22-Sep-2020
https://doi.org/10.3390/sym12091566
Zhang ZKudo YMurai TRen Y(2019)Enhancing Recommendation Accuracy of Item-Based Collaborative Filtering via Item-Variance WeightingApplied Sciences10.3390/app90919289:9(1928)Online publication date: 10-May-2019
https://doi.org/10.3390/app9091928
Albanese Md’Acierno AMoscato VPersia FPicariello A(2013)A Multimedia Recommender SystemACM Transactions on Internet Technology10.1145/253264013:1(1-32)Online publication date: 1-Nov-2013
https://dl.acm.org/doi/10.1145/2532640
Show More Cited By

Index Terms

A ranking method for multimedia recommenders
1. Applied computing
  1. Computers in other domains
    1. Digital libraries and archives
2. Information systems
  1. Information systems applications
    1. Digital libraries and archives
    2. Multimedia information systems

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Published In

cover image ACM Conferences

CIVR '10: Proceedings of the ACM International Conference on Image and Video Retrieval

July 2010

492 pages

ISBN:9781450301176

DOI:10.1145/1816041

Conference Chairs:
Shipeng Li
Microsoft Research Asia, China
,
Xinbo Gao
Xidian University, China
,
Nicu Sebe
University of Trento, Italy

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGIR: ACM Special Interest Group on Information Retrieval

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 July 2010

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CIVR' 10

Sponsor:

SIGMM

CIVR' 10: International Conference on Image and Video Retrieval

July 5 - 7, 2010

Xi'an, China

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Cited By

Shahbazi ZHazra DPark SByun Y(2020)Toward Improving the Prediction Accuracy of Product Recommendation System Using Extreme Gradient Boosting and Encoding ApproachesSymmetry10.3390/sym1209156612:9(1566)Online publication date: 22-Sep-2020
https://doi.org/10.3390/sym12091566
Zhang ZKudo YMurai TRen Y(2019)Enhancing Recommendation Accuracy of Item-Based Collaborative Filtering via Item-Variance WeightingApplied Sciences10.3390/app90919289:9(1928)Online publication date: 10-May-2019
https://doi.org/10.3390/app9091928
Albanese Md’Acierno AMoscato VPersia FPicariello A(2013)A Multimedia Recommender SystemACM Transactions on Internet Technology10.1145/253264013:1(1-32)Online publication date: 1-Nov-2013
https://dl.acm.org/doi/10.1145/2532640
Wang YLiu XNicoara ALin THsu CLi BShirmohammadi S(2012)SmartTransferProceedings of the 22nd international workshop on Network and Operating System Support for Digital Audio and Video10.1145/2229087.2229107(71-76)Online publication date: 7-Jun-2012
https://dl.acm.org/doi/10.1145/2229087.2229107
Moscato VPicariello ARinaldi AChbeir R(2010)A recommendation strategy based on user behavior in digital ecosystemsProceedings of the International Conference on Management of Emergent Digital EcoSystems10.1145/1936254.1936259(25-32)Online publication date: 26-Oct-2010
https://dl.acm.org/doi/10.1145/1936254.1936259

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