Publication Type:

Conference Paper

Source:

IEEE International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2017 - Proceedings, Institute of Electrical and Electronics Engineers Inc., p.56-59 (2017)

ISBN:

9781509059607

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027463177&doi=10.1109%2fICIMIA.2017.7975532&partnerID=40&md5=59b810f2e738749647e601b053935977

Keywords:

Artificial intelligence, Data mining, Extraction techniques, Information analysis, Information extraction techniques, Information Retrieval, Journal paper, Learning systems, Natural language processing systems, PDF document, PDF format, Research papers, Semi structured data, Text extraction

Abstract:

Text extraction is a crucial stage of analyzing Journal papers. Journal papers generally are in PDF format which is semi structured data. Journal papers are presented into different sections like Introduction, Methodology, Experimental setup, Result and analysis etc. so that it is easy to access information from any section as per the reader's interest. The main importance on section extraction is to find a representative subset of the data, which contains the information of the entire set. Various approaches to extract sections from research papers include stastical methods, NLP, Machine Learning etc. In this paper we present review of various extraction techniques from a PDF document. © 2017 IEEE.

Notes:

cited By ; Conference of 2017 IEEE International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2017 ; Conference Date: 21 February 2017 Through 23 February 2017; Conference Code:129110

Cite this Research Publication

K. Jayaram and Sangeeta, K., “A review: Information extraction techniques from research papers”, in IEEE International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2017 - Proceedings, 2017, pp. 56-59.

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