Object-oriented Modelling with Words

نویسندگان

  • Jonathan Rossiter
  • Tru H. Cao
  • Trevor P. Martin
  • James F. Baldwin
چکیده

Object-oriented modelling with words seeks to extend the new field of modelling with words, itself derived form computing with words, with features of object-oriented knowledge representation and programming. We show that object-oriented modelling with words has two key benefits; firstly the uncertain class hierarchy provides a natural knowledge representation framework for real-world problems, and secondly the object-oriented paradigm enforces a strict software engineering design and implementation process. In this paper we present a new approach to object-oriented modelling with words based on a new theory of inheritance where object memberships and property applicabilities are uncertain. We present the uncertain object-oriented logic programming language Fril++ as a tool for object-oriented modelling with words. We present an example application of object-oriented modelling with words; an extendible object-oriented data browser and machine learning environment.

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تاریخ انتشار 2001