A Persian web page classifier applying a combination of content-based and context-based features

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A Persian web page classifier applying a combination of content-based and context-based features
Authors: M. Farhoodi, A. Yari, M. Mahmoudi [edit item]
Citation: International Journal of Information Studies 1 (4): 263-71. 2009 October.
Publication type: Journal article
Peer-reviewed:
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DOI: Define doi.
Google Scholar cites: Not available
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Added by Wikilit team: Added on initial load
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A Persian web page classifier applying a combination of content-based and context-based features is a publication by M. Farhoodi, A. Yari, M. Mahmoudi.


[edit] Abstract

[edit] Research questions

"There 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."

Research details

Topics: Text classification [edit item]
Domains: Computer science [edit item]
Theory type: Design and action [edit item]
Wikipedia coverage: Sample data [edit item]
Theories: "Undetermined" [edit item]
Research design: Experiment [edit item]
Data source: [edit item]
Collected data time dimension: Cross-sectional [edit item]
Unit of analysis: Article [edit item]
Wikipedia data extraction: Missing wikipedia_data_extraction [edit item]
Wikipedia page type: Article [edit item]
Wikipedia language: Persian [edit item]

[edit] Conclusion

"We 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."

[edit] Comments

"Experiment: method: linear combination of different features and adjusting the optimum weighting during classifi cation."


Further notes[edit]

Facts about "A Persian web page classifier applying a combination of content-based and context-based features"RDF feed
Added by wikilit teamAdded on initial load +
Collected data time dimensionCross-sectional +
CommentsExperiment: method: linear combination of different features and adjusting the optimum weighting during classifi cation.
ConclusionWe 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.
Google scholar urlhttp://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 authorM. Farhoodi +, A. Yari + and M. Mahmoudi +
Has domainComputer science +
Has topicText classification +
Issue4 +
MonthOctober +
Pages263-71 +
Publication typeJournal article +
Published inInternational Journal of Information Studies +
Research designExperiment +
Research questionsThere 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.
Revid482 +
SummaristASIST +
TheoriesUndetermined
Theory typeDesign and action +
TitleA Persian web page classifier applying a combination of content-based and context-based features
Unit of analysisArticle +
Volume1 +
Wikipedia coverageSample data +
Wikipedia languagePersian +
Wikipedia page typeArticle +
Year2009 +