International Journal for Modern Trends in Science and Technology ISSN: 2455-3778 |Volume No: 02 | Issue No: 02 | February 2016
Keyphrase Extraction using Neighborhood Knowledge Vonguri Spandana1 and Dr.Srinivasu Badugu2 1
PG Scholar, Department of Computer Science & Engineering, Stanley College of Engineering and Technology for Women (Affiliated to Osmania University), Hyderabad, Telangana, India
2
Associate Professor , Department of Computer Science & Engineering, Stanley College of Engineering and Technology for Women (Affiliated to Osmania University), Hyderabad, Telangana, India
Article History Received on: Accepted on: Published on: Keyword Neighborhood TF-IDF POS tagging Stemming JTEXPRO
ABSTRACT 30-01-2016 05-02-2016 16-02-2016
This paper focus on keyphrase extraction for news articles because news article is one of the popular document genres on the web and most news articles have no author-assigned keyphrases. Existing methods for single document keyphrase extraction usually make use of only the information contained in the specified document. This paper proposes to use a small number of nearest neighbor documents to provide more knowledge to improve single document keyphrase extraction. Experimental results demonstrate the good effectiveness and robustness of our proposed approach. According to experiments conducted on several documents and keyphrases we consider top 10 keyphrases are most suitable keyphrases. Copyright Š 2015 International Journal for Modern Trends in Science and Technology All rights reserved.
Keyphrase Extraction using Neighborhood Knowledge
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