Accommodating subjective vagueness through a fuzzy extension to the relational data model

نویسندگان

  • Doheon Lee
  • Myoung-Ho Kim
چکیده

Expression and processing of vagueness, which has many real world applications, are not handled effectively in the conventional relational data model. In this paper we investigate a fuzzy extension to the relational data model and propose three fuzzy relational query languages. Two of them are the Level-1 Fuzzy Relational Algebra and Level-1 Fuzzy Relational Calculus. They are fundamental query languages and serve as a theoretical framework for the fuzzy relational database. Finally, the Fuzzy Selectiue Relational Algebra is presented to express fuzzy constants and fuzzy comparators, which are more effective to represent vagueness in user queries. We show that the three proposed query languages have the same expressive powers. We also present various aspects of the proposed model and its functional advantages over the conventional relational data model.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Fuzzification of the Relational Data Model

Expression and processing of vagueness, which has many real world applications, is not handled effectively in the conventional relational model. In this paper we investigate a fuzzy extension to the relational data model and propose three fuzzy relational query languages. ‘ho of them are the Level-l Fuzzy Relational Algebra and Level-l Fmzy Relational Calculus. They are fundamental query langua...

متن کامل

Fuzzy rough set techniques for uncertainty processing in a relational database

This paper concerns the modeling of imprecision, vagueness, and uncertainty in databases through an extension of the relational model of data: the fuzzy rough relational database, an approach which uses both fuzzy set and rough set theories for knowledge representation of imprecise data in a relational database model. The fuzzy rough relational database is formally defined, along with a fuzzy r...

متن کامل

Handling uncertainty: An extension of DL-Lite with Subjective Logic

Data in real world applications is often subject to some kind of uncertainty, which can be due to incompleteness, unreliability or inconsistency. This poses a great challenge for ontology-based data access (OBDA) applications, which are expected to provide a meaningful answers to queries, even under uncertain domains. Several extensions of classical OBDA systems has been proposed to address thi...

متن کامل

A NEW APPROACH FOR PARAMETER ESTIMATION IN FUZZY LOGISTIC REGRESSION

Logistic regression analysis is used to model categorical dependent variable. It is usually used in social sciences and clinical research. Human thoughts and disease diagnosis in clinical research contain vagueness. This situation leads researchers to combine fuzzy set and statistical theories. Fuzzy logistic regression analysis is one of the outcomes of this combination and it is used in situa...

متن کامل

Vague Sets or Intuitionistic Fuzzy Sets for Handling Vague Data: Which One Is Better?

In the real world there are vaguely specified data values in many applications, such as sensor information. Fuzzy set theory has been proposed to handle such vagueness by generalizing the notion of membership in a set. Essentially, in a Fuzzy Set (FS) each element is associated with a point-value selected from the unit interval [0,1], which is termed the grade of membership in the set. A Vague ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Inf. Syst.

دوره 18  شماره 

صفحات  -

تاریخ انتشار 1993