کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10323339 | 660933 | 2005 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Neighbor-weighted K-nearest neighbor for unbalanced text corpus
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Text categorization or classification is the automated assigning of text documents to pre-defined classes based on their contents. Many of classification algorithms usually assume that the training examples are evenly distributed among different classes. However, unbalanced data sets often appear in many practical applications. In order to deal with uneven text sets, we propose the neighbor-weighted K-nearest neighbor algorithm, i.e. NWKNN. The experimental results indicate that our algorithm NWKNN achieves significant classification performance improvement on imbalanced corpora.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 28, Issue 4, May 2005, Pages 667-671
Journal: Expert Systems with Applications - Volume 28, Issue 4, May 2005, Pages 667-671
نویسندگان
Songbo Tan,