Building Semantic Kernel for Persian Text Classification with a Small Amount of Training Data

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

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