期刊名称：International Journal of Advanced Computer Research
印刷版ISSN：2249-7277
电子版ISSN：2277-7970
出版年度：2017
卷号：7
期号：30
页码：103-110
出版社：Association of Computer Communication Education for National Triumph (ACCENT)
摘要：The analyzing and extracting important information from a text document is crucial and has produced interest in the area of text mining and information retrieval. This process is used in order to notice particularly in the text. Furthermore, on view of the readers that people tend to read almost everything in text documents to find some specific information. However, reading a text document consumes time to complete and additional time to extract information. Thus, classifying text to a subject can guide a person to find relevant information. In this paper, a subject identification method which is based on term frequency to categorize groups of text into a particular subject is proposed. Since term frequency tends to ignore the semantics of a document, the term extraction algorithm is introduced for improving the result of the extracted relevant terms from the text. The evaluation of the extracted terms has shown that the proposed method is exceeded other extraction techniques.
关键词：Subject identification; Text classification; Term frequency; Term filtering; Text document.
