نویسندگان | صغری لازمی,حسین ابراهیم پور کومله,ناصر نوروزی |
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نشریه | SpringerLink Discover Applied Sciences |
شماره صفحات | 1 |
شماره مجلد | 1 |
ضریب تاثیر (IF) | ثبت نشده |
نوع مقاله | Full Paper |
تاریخ انتشار | 2019-11-08 |
رتبه نشریه | علمی - پژوهشی |
نوع نشریه | الکترونیکی |
کشور محل چاپ | ایران |
چکیده مقاله
Keywords are a collection of important words in a document that are the core topic of the discussion. This paper proposes a hybrid method for automatically extracting keywords from Persian documents and web pages. In the proposed method, firstly, based on linguistic knowledge, processing was performed at word and letter levels to optimize of the analysis. Then a new statistical features set is defined and extracted at the word level. At the final stage, keywords are determined using the SVM algorithm. Also, in this paper, due to the lack of a corpus for evaluating the methods of automatic extraction of Persian keywords, a large-scale corpus has been developed and introduced. The achieved F-measure for keywords and non-keywords are 99.89% and 99.99% respectively.
tags: Automatic keyword extraction · Natural language processing · Persian