IDEAS home Printed from https://ideas.repec.org/a/igg/jcini0/v5y2011i3p1-29.html
   My bibliography  Save this article

Semantic Manipulations and Formal Ontology for Machine Learning based on Concept Algebra

Author

Listed:
  • Yingxu Wang

    (University of Calgary, Canada)

  • Yousheng Tian

    (University of Calgary, Canada)

  • Kendal Hu

    (University of Calgary, Canada)

Abstract

Towards the formalization of ontological methodologies for dynamic machine learning and semantic analyses, a new form of denotational mathematics known as concept algebra is introduced. Concept Algebra (CA) is a denotational mathematical structure for formal knowledge representation and manipulation in machine learning and cognitive computing. CA provides a rigorous knowledge modeling and processing tool, which extends the informal, static, and application-specific ontological technologies to a formal, dynamic, and general mathematical means. An operational semantics for the calculus of CA is formally elaborated using a set of computational processes in real-time process algebra (RTPA). A case study is presented on how machines, cognitive robots, and software agents may mimic the key ability of human beings to autonomously manipulate knowledge in generic learning using CA. This work demonstrates the expressive power and a wide range of applications of CA for both humans and machines in cognitive computing, semantic computing, machine learning, and computational intelligence.

Suggested Citation

  • Yingxu Wang & Yousheng Tian & Kendal Hu, 2011. "Semantic Manipulations and Formal Ontology for Machine Learning based on Concept Algebra," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 5(3), pages 1-29, July.
    • Handle: RePEc:igg:jcini0:v:5:y:2011:i:3:p:1-29
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijcini.2011070101
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jcini0:v:5:y:2011:i:3:p:1-29. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.