Content Based Image Retrieval is a one of the most popular search methods used in large-scale databases. Comparison the query image with each image of large scale database leads to lowering the systems performance. In this article are considered different clustering algorithms. They may be used for optimizing image searching access period.

Keywords: CBIR, clustering, K-means, fuzzy C-means (FCM), Possibilistic C-means (PCM), bio inspired algorithm

It is shown that the current direction of the development of electronic document management is the transition to the information systems that support the dialog interaction with the user in natural language. This area is challenging because of exponential growth of data processed by modern information systems. Described the problem of converting verbal criteria describing properties of the required data, SQL queries, implementation of which will allow to obtain the required data. As a practical example, the selected task is the classification of employees in three clearly defined categories: ""small experience"", ""average experience"", ""great experience"". Before you create a database assumptions were adopted: the experience of employees is taken into account from 0-25 years. The time period to 7 years is an indicator of employees with low seniority. As close to a group of employees with secondary seniority are those who have work experience of 8 to 13 years; a great experience – more than 15 years. Create table ""Employees"", consisting of the following fields: id, name, Sex, Phone, notes, date of hiring, date of dismissal, work Experience in similar position, Experience just. The work deals with the queries to retrieve data based on the SELECT statement of the SQL language. Mathematically formalizing verbal filter criteria data was formalized with trapezoidal membership functions. Describes the implementation of the conversion process trapezoidal membership functions in SQL queries against a relational database. Implemented conversion mathematically consistent as the theory of fuzzy sets and the concept of relational databases (i.e. SQL standard). Compliance transformation of fuzzy set theory in the future will allow the use of operators for manipulating sets (Union, intersection, etc.), and compliance with SQL to practically implement the proposed approach by means of a broad class of relational database management systems.

Keywords: fuzzy logic, membership function, fuzzy set term, linguistic variable, database, fuzzy queries, the index of conformity,a-slice