Document Summarization Using Clustering and Text Analysis

  • Authors

    • Mrs. Shahana Bano
    • B Divyanjali
    • A K M L R V Virajitha
    • M Tejaswi
    2018-05-31
    https://doi.org/10.14419/ijet.v7i2.32.15740
  • clustering, word count, term frequency, sentence score, document summarization.
  • Document summarization is a procedure of shortening the content report with a product, so as to make the outline with the significant parts of unique record.Now a days ,users are very much tired about their works and they don’t have much time to spend reading a lot of information .they just want the maximum and accurate information which describes everything and occupies minimum space.This paper discusses an important approach for document summarization by using clustering and text analysis. In this paper, we are performing the clustering and text analytic techniques for reducing the data redundancy and for identifying similarity sentences in text of documents and grouping them in cluster based on their term frequency value of the words. Mainly these techniques help to reduce the data and documents are generated with high efficiency.

     

     

  • References

    1. [1] Multi document based summarization â€International journal of advanced research in electrical†vol3, issue 4,April 2004.

      [2] Text features weighting for summarization of documents “Inter-national journal of computer scienceâ€, Ahmed ridha,2012.

      [3] .Improving Multi document summarization via text classification “springerâ€, Trever kohn.

      [4] .Multi document summarization using A* algorithm “Internation-al journal of computer scienceâ€, Robert zaisagukas.

      [5] .Klaus zechner†A literature survey on information extraction and text summarizationâ€, computational linguistics program, carneige Mellon university,1997.

      [6] Chin-yiewlin and Eduard Hovy,†from single to multi docu-ment summarization: A prototype System and its evaluationâ€, pro-ceedings of the ACL conference, Philadelphia, PA.2002.

      [7] .Rene Arnulfo Garcia- Herandez and Yulia Ledeneva,†word sequence models for single text summarizationâ€,IEEE,2009.

      [8] .Jimmy Lin, â€summarizationâ€, Encyclopedia of database systemsHeidelberg, germany : springer- verlag, 2009.

      [9] A Machine Learning Approach to sentence ordering for multi-document summarization and its evaluation, university of Tokyo, japan.

      [10] Sentence ordering based on cluster adjacency in multi-document summarization, institute for infocomm research Singa-pore, 119613.

      [11] Text summarization using clustering technique by “Interna-tional journal of engineering trends and technologyâ€.

      [12] Multi-document summarization using TF-IDF algorithm by “International journal of engineering and computer scienceâ€.

      [13] Sentence fusion for multi-document news summarization by Regina Barzilay* Massachusetts Institute of Technology.

      [14] Towards Coherent Multi-Document SummarizationComputer Science & Engineering.

      [15] Multi-Document Summarization By Sentence Extraction *Language Technologies Institute Carnegie Mellon University.

      [16] Improving Chronological Sentence Ordering by Precedence Relation Naoaki OKAZAKI The University of Tokyo.

  • Downloads

  • How to Cite

    Shahana Bano, M., Divyanjali, B., K M L R V Virajitha, A., & Tejaswi, M. (2018). Document Summarization Using Clustering and Text Analysis. International Journal of Engineering & Technology, 7(2.32), 456-458. https://doi.org/10.14419/ijet.v7i2.32.15740