An Efficient Approach for Keyphrase Extraction from English Document
Author(s) -
Imtiaz Hossain Emu,
Asraf Uddin Ahmed,
Manowarul Islam,
Selim Al Mamun,
Md Ashraf Uddin
Publication year - 2017
Publication title -
international journal of intelligent systems and applications
Language(s) - English
Resource type - Journals
eISSN - 2074-9058
pISSN - 2074-904X
DOI - 10.5815/ijisa.2017.12.06
Subject(s) - computer science , automatic summarization , information retrieval , set (abstract data type) , natural language processing , multi document summarization , tf–idf , artificial intelligence , term (time) , physics , quantum mechanics , programming language
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 wellknown document corpus.
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