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A Persian web page classifier applying a combination of content-based and context-based features
Abstract There are many automatic classification meThere are many automatic classification methods and algorithms that have been propose for content-based or context-based features of web pages. In this paper we analyze these features and try to exploit a combination of features to improve categorization accuracy of Persian web page classification. In this work we have suggested a linear combination of different features and adjusting the optimum weighing during application. To show the outcome of this approach, we have conducted various experiments on a dataset consisting of all pages belonging to Persian Wikipedia in the field of computer. These experiments demonstrate the usefulness of using content-based and context-based web page features in a linear weighted combination.features in a linear weighted combination.
Added by wikilit team Added on initial load  +
Collected data time dimension Cross-sectional  +
Comments Experiment: method: linear combination of different features and adjusting the optimum weighting during classifi cation.
Conclusion We have proposed a method of classifying tWe have proposed a method of classifying the Persian web page documents by linear combination of different features and adjusting the optimum weighting during classifi cation. . The results achieved with the current approach are quite encouraging. In most cases, the algorithm was able to categorize each page in the most appropriate category. The few exceptions appeared due to limitations of the linguistic tools we used for extracting the words.ic tools we used for extracting the words.
Data source Experiment responses  + , Wikipedia pages  +
Google scholar url http://scholar.google.com/scholar?ie=UTF-8&q=%22A%2BPersian%2Bweb%2Bpage%2Bclassifier%2Bapplying%2Ba%2Bcombination%2Bof%2Bcontent-based%2Band%2Bcontext-based%2Bfeatures%22  +
Has author Mojgan Farhoodi + , Alireza Yari + , Maryam Mahmoudi +
Has domain Computer science +
Has topic Text classification +
Issue 4  +
Month October  +
Pages 263-71  +
Peer reviewed Yes  +
Publication type Journal article  +
Published in International Journal of Information Studies +
Research design Experiment  +
Research questions There are many automatic classifi cation mThere are many automatic classifi cation methods and algorithms that have been propose for content-based or context-based features of web pages. In this paper we analyze these features and try to exploit a combination of features to improve categorization accuracy of Persian web page classifi cation. In this work we have suggested a linear combination of different features and adjusting the optimum weighing during application.g the optimum weighing during application.
Revid 11,617  +
Theories Undetermined
Theory type Design and action  +
Title A Persian web page classifier applying a combination of content-based and context-based features
Unit of analysis Article  +
Url http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5273915&tag=1  +
Volume 1  +
Wikipedia coverage Sample data  +
Wikipedia data extraction Live Wikipedia  +
Wikipedia language Persian  +
Wikipedia page type Article  +
Year 2009  +
Creation dateThis property is a special property in this wiki. 13 March 2012 12:20:13  +
Categories Text classification  + , Computer science  + , Publications  +
Modification dateThis property is a special property in this wiki. 30 January 2014 20:19:24  +
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