• DocumentCode
    3144757
  • Title

    Knowledge reasoning in health cloud

  • Author

    Deng, Hanbing ; Zhang, Xia ; Liu, Jiren

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2011
  • fDate
    12-14 Dec. 2011
  • Firstpage
    48
  • Lastpage
    54
  • Abstract
    Keeping healthy diet and lifestyle is the most effective way to prevent disease. But usually people only know some basic physical information like height, weight, heartbeat, and so on. They have no idea whether their food habit or lifestyle will affect their health. This paper, based on the scene of health cloud, proposes a knowledge reasoning model which includes knowledge analysis module, ontology modeling module, decision engine, rule engine and semantic template. The model provides a method which can analyze the diet and lifestyle information of people. And the information can be achieved from the domain ontology which is pretreated by domains experts. With the results of semantic reasoning processes, people can get some better healthy diet and lifestyle advices. An example of health diet has been constructed to test the performance of knowledge reasoning model. The results indicate that the model can effectively work for knowledge reasoning in health cloud.
  • Keywords
    cloud computing; diseases; expert systems; health care; inference mechanisms; ontologies (artificial intelligence); decision engine; disease prevention; domain expert; domain ontology; food habit; food lifestyle information; health cloud; healthy diet; knowledge analysis module; knowledge reasoning model; ontology modeling module; rule engine; semantic reasoning process; semantic template; Analytical models; Cloud computing; Cognition; Computational modeling; Engines; Ontologies; Semantics; agent; cloud; health cloud; knowledge; ontology; reasoning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud and Service Computing (CSC), 2011 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4577-1635-5
  • Electronic_ISBN
    978-1-4577-1636-2
  • Type

    conf

  • DOI
    10.1109/CSC.2011.6138551
  • Filename
    6138551