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...

— We present a compiler and object query system for Fril++, an object-oriented logic programming language incorporating fuzzy sets and support logic. Based on Fril, the fuzzy relational inference language, Fril++ provides extensions to support full object-oriented programming in a soft computing logic programming environment. We present the design implications of Fril++, with special emphasis o...

The Structured Query Language (SQL) has been established as a standard for querying relational databases. However, users face the problem how to define their requirements for data by the exact query conditions. This work examines advantages of fuzzy queries, which provide a better representation of the user requirements by expressing imprecise conditions through linguistic terms. Further, the p...

The aim of this paper is to give guidelines on how to formalize fuzzy relational database queries using 1 2 LΠ fuzzy logic. After the short introduction, we give an overview of the 1 2 LΠ logic. In the continuation we give a brief overview of the FRDB queries and query-database similarity relation. We conclude the paper with the description of FRDB query formalization using presented definitions.

The paper presents a new approach to deal with database preference queries, where preferences are represented in the style of possibilistic logic, using symbolic weights. The symbolic weights may be processed without the need of a numerical assignment of priority. Still, it is possible to introduce a partial ordering among the symbolic weights if necessary. On this basis, four methods that have...

Motivated by the increased need for formalized representations of the field of Data Mining and the successfull results of using Formal Concept Analysis (FCA) and Ontology, we introduce in this paper our contribution in order to support flexible query in large Database using FCA and Fuzzy Ontology. We first present our new approach for automatic generation of Fuzzy Ontology of Data Mining (FODM)...

Range query processing is a common edge computing and service in the Internet of things, which can extract user-interest information from distributed devices. How to design lightweight privacy-preserving range methods remains challenging task. Existing secure approaches suffer both high communication cost long response time, makes them unsuitable for over resource-constrained In this article, w...

In this paper, it is shown that fuzzy sets and possibility theory provide an homogeneous framework for the representation of both imprecise/uncertain information and soft queries with a flexible interpretation. Incompletely known information as well as flexible query handling capabilities are expected to extend the range of applications for future database management systems. The term fuzzy dat...

We already know that Structured Query Language (SQL) is a very powerful tool. It handles data, which is crisp and precise in nature.but it is unable to satisfy the needs for data which is uncertain, imprecise, inapplicable and vague in nature. The goal of this work is to use Fuzzy techniques i.e linguistic expressions and degrees of truth whose result are presented in this paper. For this purpo...

Although the Structured Query Language (SQL) is a very powerful tool, it is unable to satisfy needs for data selection based on linguistic expressions and degrees of truth. The goal of the research whose results are presented in the paper is to capture these expressions and make them suitable for queries. For this purpose the fuzzy generalised logical condition for the WHERE part of SQL was dev...