Fuzzy Object-oriented Database Model Research Articles

Mapping fuzzy RDF(S) into fuzzy object‐oriented databases

The Resource Description Framework (RDF) and RDF Schema (RDFS), being a recommendation of World Wide Web Consortium (W3C), have been widely used to exchange and reason information about resources on the web. It is a common case that information about resources may be uncertain under an environment of open web. To deal with uncertainties in resource information, we propose, in this paper, a general fuzzy RDF(S) model, which contains a fuzzy RDFS layer and a fuzzy RDF layer. In particular, we investigate how to formally map the fuzzy RDF(S) model to the fuzzy object-oriented database model in the paper. We develop mapping rules and implement a prototype system to demonstrate the feasibility of our approach.

Formalizing fuzzy object-oriented database models using fuzzy ontologies

Full implementation of the Semantic Web requires widespread availability of (fuzzy) ontologies. In this paper, we develop a complete approach and an automated tool for formalizing fuzzy object-oriented database (FOOD) models using fuzzy ontologies (i.e., constructing fuzzy ontologies from FOOD models), and investigate how to apply the constructed fuzzy ontologies to reason on FOOD models. Firstly, we propose a complete formal definition of FOOD models, which considers most features of FOOD models. On this basis, we propose an approach for constructing fuzzy ontologies from FOOD models. The approach can transform FOOD models (including schema and object instance information) into fuzzy ontologies. We also give full proof of correctness of the construction approach, and provide a full construction example. Furthermore, we implement a prototype tool called FOOD2FOnto, which can automatically construct fuzzy ontologies from FOOD models. Some tests demonstrate that our approach actually works. Finally, the constructed fuzzy ontologies are used to reason on the FOOD models, and some reasoning rules and a reasoning example are provided.

A new weighted fuzzy grammar on object oriented database queries

Article history: Received October 1, 2011 Received in Revised form November, 14, 2011 Accepted 25 February 2012 Available online 8 March 2012 The fuzzy object oriented database model is often used to handle the existing imprecise and complicated objects for many real-world applications. The main focus of this paper is on fuzzy queries and tries to analyze a complicated and complex query to get more meaningful and closer responses. The method permits the user to provide the possibility of allocating the weight to various parts of the query, which makes it easier to follow better goals and return the target objects. © 2012 Growing Science Ltd. All rights reserved.

Algebraic operations in fuzzy object-oriented databases

The fuzzy object-oriented databases have been proposed to meet the need of dealing with fuzzy as well as complex objects. In this paper, we present a formal fuzzy object-oriented database model. Based on the semantic measure of fuzzy data, we first identify two kinds of fuzzy object redundancies, which are inclusion redundancy and equivalence redundancy, and then define three kinds of merging operation for redundancy removal. On the basis, we define some fuzzy algebraic operations for fuzzy classes and fuzzy objects. Finally, in the paper, we discuss fuzzy querying strategies and give the form of SQL-like fuzzy querying for the fuzzy object-oriented databases.

Modeling fuzzy information in UML class diagrams and object-oriented database models

Conceptual data modeling has become essential for non-traditional application areas. Some conceptual data models have been proposed as tools for database design and object-oriented database modeling. Information in real-world applications is often vague or ambiguous. Currently, a little research is underway on modeling the imprecision and uncertainty in conceptual data modeling and the conceptual design of fuzzy databases. The unified modeling language (UML) is a set of object-oriented modeling notations and a standard of the object management group (OMG) with applications to many areas of software engineering and knowledge engineering, increasingly including data modeling. This paper introduces different levels of fuzziness into the class of UML and presents the corresponding graphical representations, with the result that UML class diagrams may model fuzzy information. The fuzzy UML data model is also formally mapped into the fuzzy object-oriented database model.

A description logic approach for representing and reasoning on fuzzy object-oriented database models

With the wide utilization of description logics ( DLs), researches on applications of DLs have become the important research lines in the Semantic Web. In particular, DLs have been deeply studied in database modeling. This paper proposes a description logic approach to represent and reason on fuzzy object-oriented database (FOOD) models. After recalling some basic notions of FOOD models and a fuzzy DL called f-ALCIQ( D), we propose a kind of formal definition and semantics of FOOD models. On this basis, representation and reasoning of FOOD models with f-ALCIQ( D) is studied. We first translate a FOOD model and its corresponding database instance into an f-ALCIQ( D) knowledge base (i.e., TBox and ABox), and further implement a prototype translation tool called FOOD2DL. Then, based on the translated f-ALCIQ( D) knowledge bases, we investigate how to reason on FOOD models (e.g., consistency, subsumption, and redundancy) through the reasoning mechanism of f-ALCIQ( D). The formalization in f-ALCIQ( D) of FOOD models makes it possible to improve the ability of reasoning on database models by means of the inference services offered by fuzzy DLs.

FOOD Index: A Multidimensional Index Structure for Similarity-Based Fuzzy Object Oriented Database Models

A fuzzy object-oriented data model is a fuzzy logic-based extension to an object-oriented database model that permits uncertain data to be explicitly represented. The fuzzy object-oriented database (FOOD) model is one of the proposed models in the literature to handle uncertainty in object-oriented databases. Several kinds of fuzziness are dealt with in the FOOD model, including fuzziness at attribute level and between object and class and between class and superclass relations. The traditional index structures do not allow efficient access to both crisp and fuzzy objects for fuzzy object-oriented databases since they are not efficient enough in processing both crisp and fuzzy queries. In this study, we propose a new index structure, namely a FOOD index (FI), to deal with different kinds of fuzziness in fuzzy object-oriented databases and to support multidimensional indexing. In this paper, we describe this proposed index structure and show how it supports various types of flexible queries, and evaluate its performance for exact, range, and fuzzy queries.

Level-2 fuzzy sets and their usefulness in object-oriented database modelling

In the real world information is, for the most part, available in an imperfect form. Managing this kind of information with classical database systems brings a disadvantageous loss of data semantics along. Therefore, advanced database modelling techniques are necessary. This paper deals with a uniform and advantageous representation of both perfect and imperfect ‘real world’ information in object-oriented databases. An object-oriented data(base) modelling technique, based on the concept ‘level-2 fuzzy set’, is presented. Hereby, the focus is on the semantic definitions of the structural, as well as on the behavioural aspects of the data. It is shown how level-2 fuzzy sets can be used to generalise the concept ‘type’. Since types are generally recognised to be the basic building blocks of object-oriented database models, generalised types can be used as basic notions of fuzzy object-oriented database models. Finally, it is illustrated and discussed how the ODMG data model can be generalised to handle ‘real world’ data in a more advantageous way.