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Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology 1 Modeling Semantic Similarities in Multiple Maps Presenter : Wei-Hao Huang Authors : Laurens van der Maaten, Geoffrey Hinton EWI-ICT TR, 2009
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Intelligent Database Systems Lab N.Y.U.S.T. I. M. 2 Outlines Motivation Objectives Methodology Experiments Conclusions Comments
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Intelligent Database Systems Lab N.Y.U.S.T. I. M. 3 Motivation Semantic space models cannot faithfully represent intransitive pairwise similarities or the similarities of words that have multiple meanings. ─ Triangle inequality ─ Nearest neighbor is limited ─ Similarities are symmetric tie suit tuxedo rope knot Animal dog China North Korea
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Intelligent Database Systems Lab N.Y.U.S.T. I. M. Objectives 4 To propose multiple map SNE to solve fundamental limitations of metric spaces tie suit tuxedo rope knot tie suit tuxedo tie rope knot
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Intelligent Database Systems Lab N.Y.U.S.T. I. M. 5 Methodology Stochastic neighbor embedding Multiple maps SNE Map Map2 Map1 Map3 Data SNE Multiple maps SNE Data Mixing proportion (importance)
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Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology Stochastic neighbor embedding 6 tie suit tuxedo rope knot
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Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology Multiple map SNE 7 tie ropesuit tie animal dog
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Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology Multiple map SNE 8 A*C=1*1/2=1/2 B*C=1*1/2=1/2
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Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments Visualization Experiments ─ Florida State University word association dataset ─ Selecting 5019 words Generalization Experiments ─ To evidence their model for semantic representation ─ Training data: 80% ─ Validation data: 10% ─ Test data: 10% 9
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Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments Visualization 10
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Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 11 Sport Clothing Statue of Liberty Cheerleader Tie monarchy
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Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments Generalization 12
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Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments Comparing multiple maps SNE with other method. ─ Semantic space models ─ Semantic networks ─ Topic models 13
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Intelligent Database Systems Lab N.Y.U.S.T. I. M. Conclusions The multiple maps SNE alleviates the fundamental limitations of metric spaces. Multiple map model has characteristics that are similar to those of topic models. 14
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Intelligent Database Systems Lab N.Y.U.S.T. I. M. 15 Comments Advantages ─ Multiple maps SNE alleviates the fundamental limitations of metric spaces Applications ─ Data visualization ─ Semantic similarities
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