We consider the problem of learning to rank relevant and novel documents so as to directly maximize a performance metric called Expected Global Utility (EGU), which has several de...
Incorporating features extracted from clickthrough data (called clickthrough features) has been demonstrated to significantly improve the performance of ranking models for Web sea...
Seed selection is of significant importance for the biased PageRank algorithms such as TrustRank to combat link spamming. Previous work usually uses a small seed set, which has a ...
Query flooding is a problem existing in Peer-to-Peer networks like Gnutella. Firework Query Model solves this problem by Peer Clustering and routes the query message more intellig...
The celebrated PageRank algorithm has proved to be a very effective paradigm for ranking results of web search algorithms. In this paper we refine this basic paradigm to take into...