• DocumentCode
    3579362
  • Title

    Clustering sentences to discover events from multiple news articles using Buckshot and Fractionation

  • Author

    SaravanaPriya, D. ; Karthikeyan, M.

  • Author_Institution
    Department of IT, P.A College of Engineering and Technology Coimbatore, Tamilnadu
  • fYear
    2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Sentence Clustering is performed based on the key terms in sentences within a document or group of documents. A sentence may come under different topics in a single document with different word of similar meaning which will not be clustered correctly by using hierarchical clustering methods. Hierarchical clustering methods are robust. They are not very efficient as its time complexity is O (n2). To overcome this problem, K-means type algorithms are used, but it handles only few documents. A proposed algorithm uses both hierarchical and partitional clustering method alternatively. It increases the accuracy and reduces the time complexity for multiple news articles. It is applied to group the text spans from multiple news articles that refer to the same event.
  • Keywords
    Algorithm design and analysis; Clustering algorithms; Clustering methods; Data mining; Fractionation; Partitioning algorithms; Time complexity; Hierarchical relational clustering; Sentence clustering; semantically similar sentence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Computing Research (ICCIC), 2014 IEEE International Conference on
  • Print_ISBN
    978-1-4799-3974-9
  • Type

    conf

  • DOI
    10.1109/ICCIC.2014.7238566
  • Filename
    7238566