Building Semantic Kernel for Persian Text Classification with a Small Amount of Training Data
Publish place: Journal of Advances in Computer Research، Vol: 6، Issue: 1
Publish Year: 1393
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JACR-6-1_010
تاریخ نمایه سازی: 16 شهریور 1395
Abstract:
The original idea of semantic kernels is to use semantic features instead of terms appeared in the text document. In this article, the documents are transformed into a new k-dimensional feature space by applying Singular Value Decomposition on the Term-Document matrix and extracting
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Authors
Amir H Jadidinejad
Faculty of Computer and Information Technology Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Venus Marza
Department of Computer Engineering, West Tehran Branch, Islamic Azad University, Tehran, Iran