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SIGIR
2011
ACM
12 years 10 months ago
2011
ACM
The majority of the current information retrieval models weight the query concepts (e.g., terms or phrases) in an unsupervised manner, based solely on the collection statistics. I...
SIGIR
2011
ACM
12 years 10 months ago
2011
ACM
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...
SIGIR
2011
ACM
12 years 10 months ago
2011
ACM
The assumptions underlying the Probability Ranking Principle (PRP) have led to a number of alternative approaches that cater or compensate for the PRP’s limitations. In this pos...
SIGIR
2011
ACM
12 years 10 months ago
2011
ACM
Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...
SIGIR
2011
ACM
12 years 10 months ago
2011
ACM
In this paper, we investigate a search-based face annotation framework by mining weakly labeled facial images that are freely available on the internet. A key component of such a ...