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English
صفحه اصلی
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چهاردهمین کنفرانس بین المللی فناوری اطلاعات و دانش
Improved Weighting in the Automated Texts Classification using Fuzzy Method
نویسندگان :
Hamidreza Sadrarhami
1
S. Mohammadali Zanjani
2
Ghazanfar Shahgholian
3
1- دانشگاه آزاد اسلامی واحد نجف آباد
2- دانشگاه آزاد اسلامی واحد نجف آباد
3- دانشگاه آزاد اسلامی واحد نجف آباد
کلمات کلیدی :
Text Classification،Text Mining،Data Mining،Weighting to Keywords،TFIDF
چکیده :
In the current digital landscape, particularly on the web, there is an increasing demand for improved methods of controlling and organizing written documents. Automatic text classification, a crucial aspect of text mining, plays a significant role in managing systems effectively. The accurate weighting of keywords greatly influences the outcomes of text-mining techniques. In this article, we present an enhancement to the TFIDF weighting method, incorporating two important factors: the distribution of keywords throughout the entire text and giving priority to the opening and conclusion paragraphs based on the fuzzy method. To assess the effectiveness of our proposed approach, we classified 500 texts into 5 distinct categories. The results clearly demonstrate the advantages of our method, highlighting its superior performance.
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