Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
The stochastic approach for link-structure analysis (SALSA) and the TKC effect
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
A vector space model for automatic indexing
Communications of the ACM
PageRank, HITS and a unified framework for link analysis
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Scaling personalized web search
WWW '03 Proceedings of the 12th international conference on World Wide Web
Hierarchical clustering of WWW image search results using visual, textual and link information
Proceedings of the 12th annual ACM international conference on Multimedia
ACM Transactions on Internet Technology (TOIT)
ACM SIGKDD Explorations Newsletter
Introduction to Information Retrieval
Introduction to Information Retrieval
Proceedings of the 18th international conference on World wide web
Mining interesting locations and travel sequences from GPS trajectories
Proceedings of the 18th international conference on World wide web
Query result clustering for object-level search
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Link analysis, eigenvectors and stability
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Clustering query refinements by user intent
Proceedings of the 19th international conference on World wide web
Unsupervised image-set clustering using an information theoretic framework
IEEE Transactions on Image Processing
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When a user submits a text based query to content sharing sites like Flickr, a list of ranked result with limited refinement options are normally provided. Typical options would allow a user to rank the results in different ways such as relevancy, time, or quality respectively. The downside of such approach is that relevant results might not be of high quality while high quality results are often irrelevant. Possible ambiguity of query terms makes it even more difficult to get high quality and relevant results. In this paper we apply link based analysis to combine content and quality indicators for ranking query results in Flickr. Experiment show that our approach are able to identify high quality photos that match a query user's intention and put them at the top of the list. The precision is better than original quality based ranking and possible query expansion results. Our approach relies on a set of seed users representing content and quality preference. We prove experimentally that the ranking is not sensitive to seed user selection, which makes it very practical.