Web news classification using neural networks based on PCA
In this paper, we propose a news web page classification method (WPCM). The WPCM uses a neural network with inputs obtained by both the principal components and class profile-based features (CPBF). The fixed number of regular words from each class will be used as a feature vectors with the reduced f...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | en |
| Published: |
2002
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| Online Access: | http://eprints.utm.my/3089/1/sice02-0163.pdf http://eprints.utm.my/3089/ http://www.sice.or.jp/event/sice2002/index.html |
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| _version_ | 1845470826222059520 |
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| author | Selamat, Ali Yanagimoto, Hidekazu Omatu, Sigeru |
| author_facet | Selamat, Ali Yanagimoto, Hidekazu Omatu, Sigeru |
| author_sort | Selamat, Ali |
| building | UTM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | In this paper, we propose a news web page classification method (WPCM). The WPCM uses a neural network with inputs obtained by both the principal components and class profile-based features (CPBF). The fixed number of regular words from each class will be used as a feature vectors with the reduced features from the PCA. These feature vectors are then used as the input to the neural networks for classification. The experimental evaluation demonstrates that the WPCM provides acceptable classification accuracy with the sports news datasets. |
| format | Conference or Workshop Item |
| id | my.utm.eprints-3089 |
| institution | Universiti Teknologi Malaysia |
| language | en |
| publishDate | 2002 |
| record_format | eprints |
| spelling | my.utm.eprints-30892017-07-23T03:23:46Z http://eprints.utm.my/3089/ Web news classification using neural networks based on PCA Selamat, Ali Yanagimoto, Hidekazu Omatu, Sigeru Z665 Library Science. Information Science In this paper, we propose a news web page classification method (WPCM). The WPCM uses a neural network with inputs obtained by both the principal components and class profile-based features (CPBF). The fixed number of regular words from each class will be used as a feature vectors with the reduced features from the PCA. These feature vectors are then used as the input to the neural networks for classification. The experimental evaluation demonstrates that the WPCM provides acceptable classification accuracy with the sports news datasets. 2002 Conference or Workshop Item NonPeerReviewed application/pdf en http://eprints.utm.my/3089/1/sice02-0163.pdf Selamat, Ali and Yanagimoto, Hidekazu and Omatu, Sigeru (2002) Web news classification using neural networks based on PCA. In: Society of Instrument and Control Engineers (SICE) 2002, August 5-7, 2002, Osaka International Convention Center (Grand Cube Osaka). http://www.sice.or.jp/event/sice2002/index.html |
| spellingShingle | Z665 Library Science. Information Science Selamat, Ali Yanagimoto, Hidekazu Omatu, Sigeru Web news classification using neural networks based on PCA |
| title | Web news classification using neural networks based on PCA |
| title_full | Web news classification using neural networks based on PCA |
| title_fullStr | Web news classification using neural networks based on PCA |
| title_full_unstemmed | Web news classification using neural networks based on PCA |
| title_short | Web news classification using neural networks based on PCA |
| title_sort | web news classification using neural networks based on pca |
| topic | Z665 Library Science. Information Science |
| url | http://eprints.utm.my/3089/1/sice02-0163.pdf http://eprints.utm.my/3089/ http://www.sice.or.jp/event/sice2002/index.html |
| url_provider | http://eprints.utm.my/ |