Publication Type : Conference Paper
Publisher : IEEE
Source : 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT)
Url : https://doi.org/10.1109/icicict46008.2019.8993142
Campus : Amritapuri
School : School of Computing
Department : Computer Science and Applications
Year : 2019
Abstract : This paper presents an unsupervised approach for extracting keywords from documents and tagging of research documents with the help of extracted keywords. Keywords are useful for checking the similarity between two documents. This will help us to correctly cluster the related documents with respect to their domains. In this paper, we are describing how research papers are clustered using keywords. A report is generated with respect to the author's contribution in different domains. The system uses Keyword Extraction using Collective Node Weight for extraction of keywords, Node-Edge Rank for ranking Keywords and WordNet Similarity Measurement for tagging of Research papers.
Cite this Research Publication : MG Thushara, Anjali S, Meera Nair M, A Graph-Based Model for Keyword Extraction and Tagging of Research Documents, 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), IEEE, 2019, https://doi.org/10.1109/icicict46008.2019.8993142