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» Pairwise Preference Learning and Ranking
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WSDM
2010
ACM
211views Data Mining» more  WSDM 2010»
14 years 3 months ago
IntervalRank - Isotonic Regression with Listwise and Pairwise Constraints
Ranking a set of retrieved documents according to their relevance to a given query has become a popular problem at the intersection of web search, machine learning, and informatio...
Taesup Moon, Alex Smola, Yi Chang, Zhaohui Zheng
ECAI
2006
Springer
14 years 2 months ago
A Unified Model for Multilabel Classification and Ranking
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operate...
Klaus Brinker, Johannes Fürnkranz, Eyke H&uum...
SEKE
2004
Springer
14 years 4 months ago
Supporting the Requirements Prioritization Process. A Machine Learning approach
Requirements prioritization plays a key role in the requirements engineering process, in particular with respect to critical tasks such as requirements negotiation and software re...
Paolo Avesani, Cinzia Bazzanella, Anna Perini, Ang...
WWW
2006
ACM
14 years 11 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
IJCNN
2007
IEEE
14 years 5 months ago
Preference Learning for Category-Ranking based Interactive Text Categorization
— Category Ranking is a variant of the multi-label classification problem, in which, rather than performing a (hard) assignment to an object of categories from a predefined set...
Fabio Aiolli, Fabrizio Sebastiani, Alessandro Sper...