کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
384339 660844 2014 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Minimizer of the Reconstruction Error for multi-class document categorization
ترجمه فارسی عنوان
کمینهساز خطای بازسازی برای طبقهبندی سند چند طبقه
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

In the present article we introduce and validate an approach for single-label multi-class document categorization based on text content features. The introduced approach uses the statistical property of Principal Component Analysis, which minimizes the reconstruction error of the training documents used to compute a low-rank category transformation matrix. Such matrix transforms the original set of training documents from a given category to a new low-rank space and then optimally reconstructs them to the original space with a minimum reconstruction error. The proposed method, called Minimizer of the Reconstruction Error (mRE) classifier, uses this property, and extends and applies it to new unseen test documents. Several experiments on four multi-class datasets for text categorization are conducted in order to test the stable and generally better performance of the proposed approach in comparison with other popular classification methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 41, Issue 3, 15 February 2014, Pages 861–868
نویسندگان
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