阿拉伯语
支持向量机
计算机科学
人工智能
分类器(UML)
边缘分级机
模式识别(心理学)
空格(标点符号)
算法
语言学
操作系统
哲学
作者
Amel Ziani,Nabiha Azizi,Yamina Tlili Guiyassa
出处
期刊:Advances in intelligent systems and computing
日期:2015-01-01
卷期号:: 175-184
被引量:4
标识
DOI:10.1007/978-3-319-17996-4_16
摘要
In this paper, an Arabic Opinion Analysis system is proposed. These sorts of applications produce data with a large number of features, while the number of samples is limited. The large number of features compared to the number of samples causes over-training when proper measures are not taken. In order to overcome this problem, we introduce a new approach based on Random sub space (RSS) algorithm integrating Support vector machine (SVM) learner as individual classifiers to offer an operational system able to identify opinions presented in reader’s comments found in Arabic newspapers blogs. The main steps of this study is based primarily on corpus construction, Statistical features extraction and then classifying opinion by the hybrid approach RSS-SVM. Experiments results based on 800 comments collected from Algerian newspapers are very encouraging; however, an automatic natural language processing must be added to enhance primitives’ vector.
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