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• W1593399679 abstract "Different ranking algorithms have been proposed to fulfil the need of ranking. The problem is that most of the existing algorithms and models are just applicable on a specific data. When the data is imbalanced and heterogeneous, finding the records belonging to the minority class is significant especially in failure cases. So considering ranking as a classification problem of predicting the specific relevance score for any category, we are going to propose a generic ranking service. In this model, a metric learning based ranking model is proposed which can be used on wide range of scientific data sets. A real world imbalanced and heterogeneous data set is used to prove the efficiency of model." @default.
• W1593399679 created "2016-06-24" @default.
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• W1593399679 date "2015-06-01" @default.
• W1593399679 modified "2023-09-23" @default.
• W1593399679 title "A Generic Ranking Service on Scientific Datasets" @default.
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• W1593399679 doi "https://doi.org/10.1109/scc.2015.73" @default.
• W1593399679 hasPublicationYear "2015" @default.
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