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» Learning to Rank Using an Ensemble of Lambda-Gradient Models
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CIKM
2009
Springer
14 years 2 months ago
Learning to rank graphs for online similar graph search
Many applications in structure matching require the ability to search for graphs that are similar to a query graph, i.e., similarity graph queries. Prior works, especially in chem...
Bingjun Sun, Prasenjit Mitra, C. Lee Giles
ISBI
2009
IEEE
14 years 2 months ago
Bridging the Semantic Gap Using Ranking Svm for Image Retrieval
One of the main challenges for Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings between the high-level semantic concepts and the low-level visual features in...
Haiying Guan, Sameer Antani, L. Rodney Long, Georg...
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
12 years 3 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...
WWW
2009
ACM
14 years 8 months ago
A dynamic bayesian network click model for web search ranking
As with any application of machine learning, web search ranking requires labeled data. The labels usually come in the form of relevance assessments made by editors. Click logs can...
Olivier Chapelle, Ya Zhang
WWW
2007
ACM
14 years 8 months ago
Supervised rank aggregation
This paper is concerned with rank aggregation, the task of combining the ranking results of individual rankers at meta-search. Previously, rank aggregation was performed mainly by...
Yu-Ting Liu, Tie-Yan Liu, Tao Qin, Zhiming Ma, Han...