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» Label Ranking Methods based on the Plackett-Luce Model
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SIGIR
2011
ACM
14 years 2 months ago
Learning to rank from a noisy crowd
We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...
Abhimanu Kumar, Matthew Lease
98
Voted
ERCIMDL
2010
Springer
162views Education» more  ERCIMDL 2010»
15 years 22 days ago
Citation Graph Based Ranking in Invenio
Invenio is the web-based integrated digital library system developed at CERN. Within this framework, we present four types of ranking models based on the citation graph that comple...
Ludmila Marian, Jean-Yves LeMeur, Martin Rajman, M...
CIKM
2010
Springer
14 years 10 months ago
Rank learning for factoid question answering with linguistic and semantic constraints
This work presents a general rank-learning framework for passage ranking within Question Answering (QA) systems using linguistic and semantic features. The framework enables query...
Matthew W. Bilotti, Jonathan L. Elsas, Jaime G. Ca...
ML
2010
ACM
124views Machine Learning» more  ML 2010»
14 years 10 months ago
Large scale image annotation: learning to rank with joint word-image embeddings
Image annotation datasets are becoming larger and larger, with tens of millions of images and tens of thousands of possible annotations. We propose a strongly performing method tha...
Jason Weston, Samy Bengio, Nicolas Usunier
SIGIR
2012
ACM
13 years 2 months ago
Learning to suggest: a machine learning framework for ranking query suggestions
We consider the task of suggesting related queries to users after they issue their initial query to a web search engine. We propose a machine learning approach to learn the probab...
Umut Ozertem, Olivier Chapelle, Pinar Donmez, Emre...