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» Learning to rank on graphs
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ECML
2006
Springer
15 years 1 months ago
A Selective Sampling Strategy for Label Ranking
Abstract. We propose a novel active learning strategy based on the compression framework of [9] for label ranking functions which, given an input instance, predict a total order ov...
Massih-Reza Amini, Nicolas Usunier, Françoi...
80
Voted
WWW
2006
ACM
15 years 10 months ago
Beyond PageRank: machine learning for static ranking
Since the publication of Brin and Page's paper on PageRank, many in the Web community have depended on PageRank for the static (query-independent) ordering of Web pages. We s...
Matthew Richardson, Amit Prakash, Eric Brill
SIAMDM
2010
114views more  SIAMDM 2010»
14 years 8 months ago
Rank-Based Attachment Leads to Power Law Graphs
Abstract. We investigate the degree distribution resulting from graph generation models based on rank-based attachment. In rank-based attachment, all vertices are ranked according ...
Jeannette Janssen, Pawel Pralat
NIPS
2008
14 years 11 months ago
Global Ranking Using Continuous Conditional Random Fields
This paper studies global ranking problem by learning to rank methods. Conventional learning to rank methods are usually designed for `local ranking', in the sense that the r...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
CIKM
2004
Springer
15 years 3 months ago
Node ranking in labeled directed graphs
Our work is motivated by the problem of ranking hyperlinked documents for a given query. Given an arbitrary directed graph with edge and node labels, we present a new flow-based ...
Krishna Prasad Chitrapura, Srinivas R. Kashyap