Presentation | 2015-01-29 Metromaps as a Tool for Minimizing Human Interaction with Learning Bayesian Classifiers Marat ZHANIKEEV, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | The traditional use of Bayesian classifiers is to have one period of learning followed by continuous application of the classifier to a much wider set of documents. However, continuous use of classifiers is also common when context grows over long periods of time. In the latter case, it is common to use classifier output as a recommendation which humans can accept as is or change when the classification is wrong. This paper proposes an interface that minimizes human interaction in such environments. The core concept is based on metromaps where documents are assigned to "train lines" first while the overall certainty of classification is based on documents' affiliation with multiple lines. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | metromaps / Bayesian classification / multidimensional classification / learning automation, folksonomy / ontologies / semantic web |
Paper # | NC2014-59 |
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Conference Information | |
Committee | NC |
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Conference Date | 2015/1/22(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Neurocomputing (NC) |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Metromaps as a Tool for Minimizing Human Interaction with Learning Bayesian Classifiers |
Sub Title (in English) | |
Keyword(1) | metromaps |
Keyword(2) | Bayesian classification |
Keyword(3) | multidimensional classification |
Keyword(4) | learning automation, folksonomy |
Keyword(5) | ontologies |
Keyword(6) | semantic web |
1st Author's Name | Marat ZHANIKEEV |
1st Author's Affiliation | Computer Science and Systems Engineering Kyushu Institute of Technology() |
Date | 2015-01-29 |
Paper # | NC2014-59 |
Volume (vol) | vol.114 |
Number (no) | 437 |
Page | pp.pp.- |
#Pages | 4 |
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