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» Multiple Aspect Ranking Using the Good Grief Algorithm
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NAACL
2007
13 years 6 months ago
Multiple Aspect Ranking Using the Good Grief Algorithm
We address the problem of analyzing multiple related opinions in a text. For instance, in a restaurant review such opinions may include food, ambience and service. We formulate th...
Benjamin Snyder, Regina Barzilay
JMLR
2012
11 years 7 months ago
Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets
We propose a new method for comparing learning algorithms on multiple tasks which is based on a novel non-parametric test that we call the Poisson binomial test. The key aspect of...
Alexandre Lacoste, François Laviolette, Mar...
SIGMOD
2011
ACM
234views Database» more  SIGMOD 2011»
12 years 7 months ago
Ranking with uncertain scoring functions: semantics and sensitivity measures
Ranking queries report the top-K results according to a user-defined scoring function. A widely used scoring function is the weighted summation of multiple scores. Often times, u...
Mohamed A. Soliman, Ihab F. Ilyas, Davide Martinen...
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
12 years 12 days 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...
CIKM
2000
Springer
13 years 9 months ago
Boosting for Document Routing
RankBoost is a recently proposed algorithm for learning ranking functions. It is simple to implement and has strong justifications from computational learning theory. We describe...
Raj D. Iyer, David D. Lewis, Robert E. Schapire, Y...