文章基本信息

标题：Named Entity Recognition for Nepali Text Using Support Vector Machines
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作者：Surya Bahadur Bam ; Tej Bahadur Shahi
期刊名称：Intelligent Information Management
印刷版ISSN：2150-8194
电子版ISSN：2150-8208
出版年度：2014
卷号：6
期号：2
页码：21-29
DOI：10.4236/iim.2014.62004
出版社：Scientific Research Publishing
摘要：Named Entity Recognition aims to identify and to classify rigid designators in text such as proper names, biological species, and temporal expressions into some predefined categories. There has been growing interest in this field of research since the early 1990s. Named Entity Recognition has a vital role in different fields of natural language processing such as Machine Translation, Information Extraction, Question Answering System and various other fields. In this paper, Named Entity Recognition for Nepali text, based on the Support Vector Machine (SVM) is presented which is one of machine learning approaches for the classification task. A set of features are extracted from training data set. Accuracy and efficiency of SVM classifier are analyzed in three different sizes of training data set. Recognition systems are tested with ten datasets for Nepali text. The strength of this work is the efficient feature extraction and the comprehensive recognition techniques. The Support Vector Machine based Named Entity Recognition is limited to use a certain set of features and it uses a small dictionary which affects its performance. The learning performance of recognition system is observed. It is found that system can learn well from the small set of training data and increase the rate of learning on the increment of training size.
关键词：Support Vector Machine; Named Entity Recognition; Machine Learning; Classification; Nepali Language Text