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- W2520908266 abstract "Classification results are not unique and can vary according to the user’s viewpoint. If a document classification system ignores the user’s viewpoints, classification will be different from the result desired by the user, and the difference between the user’s desired result and the system’s produced result can cause some inhibitions and oversights in information retrieval. Extracting the user’s viewpoints from the classification examples performed preliminarily by the user allows us to configure classifications that reflect the user’s desire. In this study, we propose four methods to extract viewpoints and three methods to classify documents using Nonnegative Matrix Factorization (NMF) matrix decomposition. We exhibit the results of comparative experiments with the original NMF, Semi-Supervised NMF (SSNMF) and our proposed methods." @default.
- W2520908266 created "2016-09-23" @default.
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- W2520908266 date "2015-01-01" @default.
- W2520908266 modified "2023-09-30" @default.
- W2520908266 title "Document Classification using Matrix Decomposition with Varied Viewpoints" @default.
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- W2520908266 doi "https://doi.org/10.52731/iee.v1.i4.27" @default.
- W2520908266 hasPublicationYear "2015" @default.
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