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Mining adjacent markets from a large-scale ads video collection for image advertising

Authors:

Guwen Feng,

Xin-Jing Wang,

Lei Zhang,

Wei-Ying MaAuthors Info & Claims

SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval

Pages 893 - 894

https://doi.org/10.1145/1835449.1835669

Published: 19 July 2010 Publication History

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Abstract

The research on image advertising is still in its infancy. Most previous approaches suggest ads by directly matching an ad to a query image, which lacks the power to identify ads from adjacent market. In this paper, we tackle the problem by mining knowledge on adjacent markets from ads videos with a novel Multi-Modal Dirichlet Process Mixture Sets model, which is a unified model of (video frames) clustering and (ads) ranking. Our approach is not only capable of discovering relevant ads (e.g. car ads for a query car image), but also suggesting ads from adjacent markets (e.g. tyre ads). Experimental results show that our proposed approach is fairly effective.

References

[1]

Z. Ghahramani, and K. A. Heller. Bayesian Sets. Neural Information Processing Systems (NIPS). 2005.

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[2]

T. Mei, X.-S. Hua, and S.-P. Li. Contextual In-Image Advertising. 2008.

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[3]

A. Velivelli, and T.S. Huang. Automatic Video Annotation Using Multimodal Dirichlet Process Mixture Model. ICNSC 2008.

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[4]

X.-J. Wang, M. Yu, et al. Argo: Intelligent Advertising by Mining a User's Interest from His Photo Collections, in conjunction with SIGKDD (ADKDD), Paris, 2009.

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Index Terms

Mining adjacent markets from a large-scale ads video collection for image advertising
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
2. Mathematics of computing
  1. Probability and statistics
    1. Nonparametric statistics

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Published In

SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval

July 2010

944 pages

ISBN:9781450301534

DOI:10.1145/1835449

General Chairs:
Fabio Crestani
University of Lugano, CH
,
Stéphane Marchand-Maillet
University of Geneva, CH
,
Program Chairs:
Hsin-Hsi Chen
National Taiwan University, TW
,
Efthimis N. Efthimiadis
University of Washington, USA
,
Jacques Savoy
University of Neuchatel, CH

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Association for Computing Machinery

New York, NY, United States

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Published: 19 July 2010

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SIGIR '10: The 33rd International ACM SIGIR conference on research and development in Information Retrieval

July 19 - 23, 2010

Geneva, Switzerland

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SIGIR '10 Paper Acceptance Rate 87 of 520 submissions, 17%;

Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Contextual in-image advertising

Video ads dissemination through WiFi-cellular hybrid networks

Scalability of an Ad Hoc On-Demand Routing Protocol in Very Large-Scale Mobile Wireless Networks

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