期刊名称：International Journal of Intelligent Systems and Applications
印刷版ISSN：2074-904X
电子版ISSN：2074-9058
出版年度：2017
卷号：9
期号：12
页码：59-66
DOI：10.5815/ijisa.2017.12.06
出版社：MECS Publisher
摘要：Keyphrases are set of words that reflect the main topic of interest of a document. It plays vital roles in document summarization, text mining, and retrieval of web contents. As it is closely related to a document, it reflects the contents of the document and acts as indices for a given document. Extracting the ideal keyphrases is important to understand the main contents of the document. In this work, we present a keyphrase extraction method that efficiently finds the keywords from English documents. The methods use some important features of the document such as TF, TF*IDF, GF, GF*IDF, TF*GF*IDF for the purpose. Finally, the performance of the proposal is evaluated using well-known document corpus.
关键词：Keypharse;Stemming;Keyphrase Nomination;Term Frequency;Inverse Document Frequency
