• DocumentCode
    2349252
  • Title

    A Dynamic Task-Model Induction Model Based Induction Mining on Large and High Dimension Data

  • Author

    Sunitha, G. ; Reddy, A. Rama Mohan ; Sriharsha, A.V.

  • Author_Institution
    Narayana Eng. Coll., Nellore, India
  • fYear
    2009
  • fDate
    27-28 Oct. 2009
  • Firstpage
    741
  • Lastpage
    743
  • Abstract
    The process of modeling concerns itself with the extraction organization of knowledge unambiguously. The rapid advancements in information processing systems are steering engineering research towards the development of intelligent systems. Though the aim of modeling is to provide the human user of the environment to represent knowledge that is convenient to operate, Modeling has become indispensable using sophisticated and automated tool. The algorithmic model represents the functional form of the system. The evolutionary model brings the phenomenal behavior of nature into practice. The proposition and relocation of the model in the process of knowledge discovery is becoming imperative as the complex processes and varied data sets. The attempt has been made to design a dynamic task-model and its induction in the process of knowledge discovery.
  • Keywords
    data mining; information systems; knowledge representation; task analysis; high dimension data; information processing systems; knowledge discovery; knowledge extraction; knowledge representation; large dimension data; model based induction mining; task-model induction; Application software; Communications technology; Data engineering; Data mining; Data models; Educational institutions; Humans; Information processing; Intelligent systems; Knowledge engineering; agility; design; induction methods; knowledge discovery; model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Recent Technologies in Communication and Computing, 2009. ARTCom '09. International Conference on
  • Conference_Location
    Kottayam, Kerala
  • Print_ISBN
    978-1-4244-5104-3
  • Electronic_ISBN
    978-0-7695-3845-7
  • Type

    conf

  • DOI
    10.1109/ARTCom.2009.226
  • Filename
    5328828