Information Extraction from Research Papers Based on Statistical Methods

  • Selvani Deepthi Kavila
  • D. Fathima Rani
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 381)


In the research field we require more time to read a single research paper; it also consumes more time to find the algorithms and limitations of the paper. So we require a fast reading system to identify this problem. This paper identifies the algorithms or techniques, or methods, and limitations of a research paper, and also classifies the area of the algorithm. Key phrases are sets of words that elucidate the relationship between context and content in the document. Key phrases are identified from the document and algorithms or techniques, or methods of that paper are extracted. Keywords are a subset of words that contain important information and the area is classified. Cue words are those that contain meaningful information used to identify the limitations of the paper.


Text mining Information extraction Key phrase extraction Key words Cue words 


  1. 1.
    Pacheri Bari, J.: Introduction of text mining and analysis of text mining techniques. Indian J. Res. 2(2) (2013). Singhania UniversityGoogle Scholar
  2. 2.
    Gupta, V., Lehal, G.S.: A survey of text mining techniques and applications. J. Emerg. Technol. Web Intell. 1(1), 60–76 (2009)Google Scholar
  3. 3.
    Sai Hari Priyanka, J.S.V., Sharmila Rani, J., Deepthi, K.S., Kranthi, T.: Information tracking from research papers using classification techniques. In: Satapathy, S.C. et al. (ed.) Emerging ICT for Bridging the Future, vol. 1, 153 Advances in Intelligent Systems and Computing 33. Springer, Switzerland (2015)Google Scholar
  4. 4.
    Wan, X., Xiao, J.: Single document keyphrase extraction using neighborhood knowledge. In: Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (2008)Google Scholar
  5. 5.
    Mooney, R.J., Nahm, U.Y.: Text mining with information extraction. In: Daelemans, W., du Plessis, T., Snyman, C., Teck, L. (eds.) Electronic Language Management: Proceedings of the 4th International MIDP Colloquium, September 2003, pp. 141–160. Bloemfontein, South Africa, Van Schaik Pub., South Africa (2005)Google Scholar
  6. 6.
    Zhang, C., Wang, H., Liu, Y., Wu, D., Liao, Y., Wang, B.: Automatic keyword extraction from documents using conditional random fields. J. Comput. Inf. Syst. 4(3), 1169–1180 (2008)Google Scholar
  7. 7.
    Menaka, S., Radha, N.: Text classification using keyword extraction technique. Int. J. Adv. Res. Comput. Sci. Eng. 3(12) 2013Google Scholar
  8. 8.
    Joshi, A., Kaur, R.: Keyphrase Extraction in scientific articles: a supervised approach. Piaki Bhaskar Kishorjit Nongmeikapam Sivaji Bandyopadhyay 3(3) 2013Google Scholar
  9. 9.
    Turney, P.: Learning to extract key phrases from text. National Research Council of Canada. Kim, S.N., Kan. M.Y. Technical report (2009)Google Scholar
  10. 10.
    Hanyurwimfura, D., Liao, B., Njogu, H., Ndatinya, E.: An automated cue word based text extraction. J. Converg. Inf. Technol. 7(10) June 2012 doi: 10.4156/jcit.vol7.issue10.50
  11. 11.
    Amini, M.-R., Usunier, N.: A Review: Comparative Study of Various Clustering Techniques in Data Mining. SIGIR’09, July 19.23, 2009, Boston, Massachusetts, USA ACM 978-1-60558-483-6/09/07Google Scholar
  12. 12.
    Sarkar, K., Nasipuri, M., Ghose, S.: A new approach to keyphrase extraction using neural networks. Int. J. Comput. Sci. Issues 7(2), (2010)Google Scholar
  13. 13.
    Jadhav Bhushan, G., Warke Pushkar, U., Kuchekar Shivaji, P., Kadam Nikhil, V.: Incorporating prior knowledge into a transductive ranking algorithm for multi-document summarization. Int. J. Emerg. Technol. Adv. Eng. (ISSN 2250-2459, ISO 9001:2008), 4(4) (2014)
  14. 14.
    Jadhav Bhushan, G., Warke Pushkar, U., Kuchekar Shivaji, P., Kadam Nikhil, V.: Searching research papers using clustering and textmining. Int. J. Emerg. Technol. Adv. Eng. 4(4) (2014) (ISSN 2250-2459, ISO 9001:2008)

Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringAnil Neerukonda Institute of Technology and SciencesVisakhapatnamIndia

Personalised recommendations