Extracting thematic information from scientific papers has wide applications in information retrieval systems. Keywords give compact representation of a document. This paper proposes a document centered approach for automatic keyword extraction and domain classification of research articles. Here we induce a hybrid approach by adopting different methods in various phases of the system. Domain classification is important for researchers to identify the articles within their interest. The proposed system uses Rapid Automatic Keyword Extraction (RAKE) algorithm for automatic keyphrase extraction which gives best score of keywords. The classification process concerns semantic analysis which includes keyword-score matrix and cosine similarity. A comparative study of performance of RAKE algorithm which uses score-matrix against KEA algorithm based on term frequencies to extract relevant keyword was also performed.
Thushara M. G., MS, K., and Nair, S. S., “Domain Classification and Tagging of Research Papers using Hybrid Keyphrase Extraction Method”, ICACNI 2017 : 5th International Conference on Advanced Computing, Networking, and Informatics, At National Institute of Technology. Goa, 2017.