The Journal of Machine Learning Research
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Finding advertising keywords on web pages
Proceedings of the 15th international conference on World Wide Web
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
A semantic approach to contextual advertising
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
vADeo: video advertising system
Proceedings of the 15th international conference on Multimedia
VideoSense: towards effective online video advertising
Proceedings of the 15th international conference on Multimedia
Just-in-time contextual advertising
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Contextual advertising by combining relevance with click feedback
Proceedings of the 17th international conference on World Wide Web
Keyword extraction for contextual advertisement
Proceedings of the 17th international conference on World Wide Web
Contextual in-image advertising
MM '08 Proceedings of the 16th ACM international conference on Multimedia
A New Baseline for Image Annotation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Bid optimization for broad match ad auctions
Proceedings of the 18th international conference on World wide web
Catching the drift: learning broad matches from clickthrough data
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Heterogeneous transfer learning for image clustering via the social web
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Modern Information Retrieval
A Wikipedia Matching Approach to Contextual Advertising
World Wide Web
NLDB'09 Proceedings of the 14th international conference on Applications of Natural Language to Information Systems
JIST'11 Proceedings of the 2011 joint international conference on The Semantic Web
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In recent years, more and more images have been uploaded and published on the Web. Along with text Web pages, images have been becoming important media to place relevant advertisements. Visual contextual advertising, a young research area, refers to finding relevant text advertisements for a target image without any textual information (e.g., tags). There are two existing approaches, advertisement search based on image annotation, and more recently, advertisement matching based on feature translation between images and texts. However, the state of the art fails to achieve satisfactory results due to the fact that recommended advertisements are syntactically matched but semantically mismatched. In this paper, we propose a semantic approach to improving the performance of visual contextual advertising. More specifically, we exploit a large high-quality image knowledge base (ImageNet) and a widely-used text knowledge base (Wikipedia) to build a bridge between target images and advertisements. The image-advertisement match is built by mapping images and advertisements into the respective knowledge bases and then finding semantic matches between the two knowledge bases. The experimental results show that semantic match outperforms syntactic match significantly using test images from Flickr. We also show that our approach gives a large improvement of 16.4% on the precision of the top 10 matches over previous work, with more semantically relevant advertisements recommended.