Alexander Ryjov

Fuzzy Linguistic Scales: Definition, Properties and Applications

This paper studies the mathematical aspects of a formalized description of the humans acting as measuring devices. It is assumed that the person describes the real object properties in the form of linguistic values. The subjective degree of convenience of such a description depends on the selection and the composition of such linguistic values.

Basic Principles and Foundations of Information Monitoring Systems

IMS works with diverse, multi-level, fragmentary, unreliable, and varying in time information about some problem/process and allows performing monitoring of the problem/process evolution and working out strategic plans of the problem/process development.

Automation of Knowledge Work: A Framework of Soft Computing

Modern information technologies have changed our world dramatically during last years. We see how a number of traditional professions were died, and how a number of new specialties and workplaces were born under pressure of new technologies. Technologies are moving so quickly, and in so many directions, that it becomes challenging to even keep in mind a general picture. In this article, we shortly discuss one of the most visible disruptive technologies – automation of knowledge work, and tried to formulate our vision why and how we can use soft computing framework in this area. Main ideas are illustrated on a very core activity in every society – smart learning for education.

Towards an Optimal Task-Driven Information Granulation

In this work we have analyzed Big Data sources and made a conclusion that sizeable part of them is people-generated data. We can present this type of data in form of qualitative attributes. The model of such attributes is a collection of fuzzy granules. We also need to granulate the data for application of a big part of analytical technologies. When we form the granules, we have a choice among different variants. Which of them is good for specific task? How can we measure this “goodness” and make a choice the best (optimal) granulation? We provide our vision of answers on these questions in the chapter.

Personalization of Social Networks: Adaptive Semantic Layer Approach

This work describes the idea of an adaptive semantic layer for large-scale databases, allowing to effectively handle a large amount of information. This effect is reached by providing an opportunity to search information on the basis of generalized concepts, or in other words, linguistic descriptions. These concepts are formulated by the user in natural language, and modelled by fuzzy sets, defined on the universe of the significances of the characteristics of the data base objects. After adjustment of user’s concepts based on search results, we have “personalized semantics” for all terms which particular person uses for communications with data base or social networks (for example, “young person” will be different for teenager and for old person; “good restaurant” will be different for people with different income, age, etc.).

On optimal fuzzy information granulation

Information granulation is one of the basic concept of human cognition. L.A. Zadeh defined the subject of the theory of fuzzy information granulation by the following way “The theory of fuzzy information granulation (TFIG) is inspired by the ways in which humans granulate information and reason with it. However, the foundations of TFIG and its methodology are mathematical in nature” [7].

The measure of uncertainty of fuzzy set's collection: Definition, properties and applications

The theory of fuzzy sets is known to be an instrument for the management of uncertainty. The authors objective is to introduce the concept of fuzziness degree, which is a measure of uncertainty, of some collection of fuzzy sets, and to describe its practical applications. The collection of fuzzy sets is defined. Such structures can be interpreted as a set of values of some fuzzy linguistic scale, or as a set of different alternatives in problem solving and decision-making, or as a description of classes in fuzzy classification and clustering, or as a representation of term-sets of linguistic values etc. The problems of using the results in information retrieval systems are discussed.<<ETX>>

Information communication system for supporting of market 'ELEPHANT'

The authors tried to analyze different systems for commercial information processing. The main task of such systems is to compare different offers. Usually the problem is solved by using classifiers of goods. This method has some negative aspects, and an attempt was made to overcome them by comparison of texts of commercial offers and calculation criteria of their likenesses. An uncertainty, obtained after such a comparison was analyzed and handled by a special algorithm. A new system of commercial data processing called ELEPHANT that operates on the basis of this hybrid algorithm and the results of its use in the Department of Defense Industry of Russia are described. The problem of expansion of this method for use in several regional commercial networks is discussed.<<ETX>>

Personalization and Optimization of Information Retrieval: Adaptive Semantic Layer Approach

This work describes the idea of an adaptive semantic layer for large-scale databases, allowing to effectively handling a large amount of information. This effect is reached by providing an opportunity to search information on the basis of generalized concepts, or in other words, linguistic descriptions. These concepts are formulated by the user in natural language, and modelled by fuzzy sets, defined on the universum of the significances of the attributes of the database. After adjustment of user’s concepts based on search results, we have “personalized semantics” for all terms which particular person uses for communications with database (for example, “young person” will be different for teenager and for old person; “good restaurant” will be different for people with different income, age, etc.).

From energy storage to EnerNet: Smart grid for abundant energy

We see two major pains today: new energy sources and energy storage. BG Partners Group and SGiM work on breakthrough solutions to directly address both problems with our proprietary products and in collaboration with our strategic partners. We focus on environmentally friendly fuel cells for distributed, reliable, high quality energy generation and storage as well as heating-cooling cogeneration - from mobile to residential and grid level applications. Using Silicon Valley style effective product incubation platforms, we emphasize and illustrate a hybrid innovation model which combines the two best commercialization approaches - corporate labs and venture capital funded start-ups. In closing, there is a note on the new manufacturing and regional policies and strategies currently active in re-shaping the energy landscape.