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SIGIR
2012
ACM
11 years 9 months ago
Inferring missing relevance judgments from crowd workers via probabilistic matrix factorization
In crowdsourced relevance judging, each crowd worker typically judges only a small number of examples, yielding a sparse and imbalanced set of judgments in which relatively few wo...
Hyun Joon Jung, Matthew Lease
CIVR
2006
Springer
186views Image Analysis» more  CIVR 2006»
13 years 10 months ago
Leveraging Active Learning for Relevance Feedback Using an Information Theoretic Diversity Measure
Abstract. Interactively learning from a small sample of unlabeled examples is an enormously challenging task. Relevance feedback and more recently active learning are two standard ...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...
21
Voted
TREC
2004
13 years 8 months ago
From the Texts to the Contexts They Contain: A Chain of Linguistic Treatments
The text-mining system we are building deals with the specific problem of identifying the instances of relevant concepts present in the texts. Therefore, our system relies on inte...
Ahmed Amrani, Jérôme Azé, Thom...
ICPR
2008
IEEE
14 years 8 months ago
Learning weighted distances for relevance feedback in image retrieval
We present a new method for relevance feedback in image retrieval and a scheme to learn weighted distances which can be used in combination with different relevance feedback metho...
Enrique Vidal, Hermann Ney, Roberto Paredes, Thoma...
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
12 years 2 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...