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SIGIR
2012
ACM
13 years 4 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
SIGIR
2002
ACM
15 years 1 months ago
Video retrieval using an MPEG-7 based inference network
This work proposes a model for video retrieval based upon the inference network model. The document network is constructed using video metadata encoded using MPEG-7 and captures i...
Andrew Graves, Mounia Lalmas
UAI
1996
15 years 3 months ago
Asymptotic Model Selection for Directed Networks with Hidden Variables
We extend the Bayesian Information Criterion (BIC), an asymptotic approximation for the marginal likelihood, to Bayesian networks with hidden variables. This approximation can be ...
Dan Geiger, David Heckerman, Christopher Meek
KDD
2003
ACM
217views Data Mining» more  KDD 2003»
16 years 2 months ago
Algorithms for estimating relative importance in networks
Large and complex graphs representing relationships among sets of entities are an increasingly common focus of interest in data analysis--examples include social networks, Web gra...
Scott White, Padhraic Smyth
NIPS
2001
15 years 3 months ago
The Intelligent surfer: Probabilistic Combination of Link and Content Information in PageRank
The PageRank algorithm, used in the Google search engine, greatly improves the results of Web search by taking into account the link structure of the Web. PageRank assigns to a pa...
Matthew Richardson, Pedro Domingos