An approach to calculate the relational division in fuzzy databases is presented, starting with the GEFRED model. The tuples of the division are obtained with a possibility degree that indicates the extent to which they comply with the relational division requisites. The results obtained are those expected a priori. Furthermore, in order to formalize this method of fuzzy relational division, tw...

A study on fuzzy relational visualization in system development aspects is presented. The front-end enables dynamic and scalable changes in visualization according to user’s expertise and inspiration. Integrative management of various data and knowledge is handled by the back-end at any scale in cloud computing environment. Extended Logic Programming is used as the core of fuzzy relational mana...

We present an overview of the most important proposals for human-oriented query languages for relational databases, based on fuzzy sets theory. To highlight important issues concerning communication with databases, we propose two taxonomies: the first taxonomy deals with flexible query languages in crisp relational databases and the second deals with flexible query languages in fuzzy relational...

As moving to big data world where data is increasing in unstructured way with high velocity, there is a need of data-store to store this bundle amount of data. Traditionally, relational databases are used which are now not compatible to handle this large amount of data, so it is needed to move on to non-relational data-stores. In the current study, we have proposed an extension of the Mongo...

This paper presents new algorithms (Fuzzy c-Medoids or FCMdd and Robust Fuzzy c-Medoids or RFCMdd) for fuzzy clustering of relational data. The objective functions are based on selecting c representative objects (medoids) from the data set in such a way that the total fuzzy dissimilarity within each cluster is minimized. A comparison of FCMdd with the well-known Relational Fuzzy c-Means algorit...

-The traditional query in relational database is unable to satisfy the needs for dealing with fuzzy linguistic values. In this paper, a new data query technique composed of fuzzy theory and MS-SQL is provided. Here, the query can be implemented for fuzzy linguistic variables query via an interface to Microsoft ASP.NET. It is being applied to an realistic instance i.e. questions could be express...

Fuzzy queries addressed to a relational database management system are based on the expression of user preferences which leads to obtain more appropriate answers. Fuzzy set theory provides powerful tools to define such conditions (fuzzy conditions). In this context, it is possible to consider fuzzy bipolar conditions which are made of two fuzzy sets to describe user's preferences: i) a fuzzy co...

In this paper, a subtractive relational fuzzy c-medoids clustering approach is discussed to identify web user session clusters from weblogs, based on their browsing behavior. In this approach, the internal arrangement of data along with the density of pairwise dissimilarity values is favored over arbitrary starting estimations of medoids as done in the conventional relational fuzzy c-medoids al...

In this paper, optimization of a linear objective function with fuzzy relational inequality constraints is investigated where the feasible region is formed as the intersection of two inequality fuzzy systems and Hamacher family of t-norms is considered as fuzzy composition. Hamacher family of t-norms is a parametric family of continuous strict t-norms, whose members are decreasing functions of ...

Many real world systems and applications must deal with imprecise or vague data. For such systems, information management components are needed that provide support for managing this imprecise data. Fuzzy theory allows us to model imprecise or vague data. The use of fuzzy theory also allows us to model vague knowledge. There have been several proposals for extending relational database systems ...