The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Rank aggregation methods for the Web
Proceedings of the 10th international conference on World Wide Web
Modern Information Retrieval
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
SIAM Journal on Discrete Mathematics
An efficient boosting algorithm for combining preferences
The Journal of Machine Learning Research
Link fusion: a unified link analysis framework for multi-type interrelated data objects
Proceedings of the 13th international conference on World Wide Web
Discriminative models for information retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Object-level ranking: bringing order to Web objects
WWW '05 Proceedings of the 14th international conference on World Wide Web
Learning to rank using gradient descent
ICML '05 Proceedings of the 22nd international conference on Machine learning
Classification of digital photos taken by photographers or home users
PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part I
Adaptive search engines as discovery games: an evolutionary approach
Proceedings of the 6th International Conference on Advances in Mobile Computing and Multimedia
Estimation of Geographic Relevance for Web Objects Using Probabilistic Models
W2GIS '08 Proceedings of the 8th International Symposium on Web and Wireless Geographical Information Systems
Community Adaptive Search Engines
International Journal of Advanced Intelligence Paradigms
| Hi-index | 0.00 |
Vertical search is a promising direction as it leverages domain-specific knowledge and can provide more precise information for users. In this paper, we study the Web object-ranking problem, one of the key issues in building a vertical search engine. More specifically, we focus on this problem in cases when objects lack relationships between different Web communities, and take high-quality photo search as the test bed for this investigation. We proposed two score fusion methods that can automatically integrate as many Web communities (Web forums) with rating information as possible. The proposed fusion methods leverage the hidden links discovered by a duplicate photo detection algorithm, and aims at minimizing score differences of duplicate photos in different forums. Both intermediate results and user studies show the proposed fusion methods are practical and efficient solutions to Web object ranking in cases we have described. Though the experiments were conducted on high-quality photo ranking, the proposed algorithms are also applicable to other ranking problems, such as movie ranking and music ranking.