A knowledge based system for automatic classification of web pages
The paper describes design and implementation of a new knowledge based system for Automatic Information Retrieval DataBase (AIRDB).AIRDB helps the end-user to cluster and classify web pages on the basis of information filtering combined with an Artificial Neural Network (ANN).The classification de...
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| 主要作者: | |
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| 格式: | Conference or Workshop Item |
| 語言: | English |
| 出版: |
2006
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| 主題: | |
| 在線閱讀: | http://repo.uum.edu.my/11537/1/564.pdf http://repo.uum.edu.my/11537/ http://www.kmice.cms.net.my/ |
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| 總結: | The paper describes design and implementation of a new knowledge based system for
Automatic Information Retrieval DataBase (AIRDB).AIRDB helps the end-user to cluster and classify web pages on the basis of information filtering combined with an
Artificial Neural Network (ANN).The classification depends mainly on keyword indexes.A large sample set consists of 11043 web pages of several formats are collected automatically and randomly from various resources.The AIRDB feature selection algorithm is summarized.The feature selection depends upon stemming words of web page. Each stem word is generated with local profile. This local profile contains information that indicates the weight of each stem with the possible related classes of web pages.A statistical analysis process is illustrated to reduce the noise stems.The various components of the AIRDB are described.The knowledge based system is tested with various web pages that disseminate their content
in English.The average discrimination performance of the AIRDB reaches 84%. |
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