Gennady Osipov

Intelligent system for fish stock prediction and allowable catch evaluation

Abstract The paper describes an intelligent system for evaluation and prediction of marine fish stocks and determination of allowable quotas. The system can forecast population abundance and biomass, possible total allowable catch, determine the quota allocation to subjects of fishery, based on various criteria. As knowledge sources, the system uses the results of long-term observations and research, regular dependencies established by experts, and human experts themselves. As initial data, monitoring and sampling results are used. Practical use of the system in 1995–1997 demonstrated satisfactory agreement between the values predicted by the system and the actual population characteristics. The system has been developed using SIMER+MIR intelligent techniques (Osipov, G.S., Gukova, S.M., Komarov, S.I., Kurshev, E.P., 1987. Expert system tools for badly structured fields. In: Plander, I. (Ed.), Artificial Intelligence and Information-Control Systems of Robots-87. North-Holland, Amsterdam).

Relational-situational method for text search and analysis and its applications

A relational-situational method for analysis of natural language texts is outlined based on the theory of communicative grammar of the Russian language and the theory of heterogeneous semantic networks. It is shown that the relational-situational method can be used for precise search of documents in local and globalnets and electronic libraries

Dynamics in integrated knowledge-based systems

The paper studies the behavior of knowledge-based integrated systems with quasi-axiomatic state description. A mechanism for state closure is considered. Concepts of knowledge base deductive and causal completeness are introduced, and their relationship with behavior and controllability of integrated systems is established.

Application of linguistic knowledge to search precision improvement

The paper presents methods for semantically relevant search. The authors mainly focus on the usage of linguistic approach to improvement of search precision in search engines. The effectiveness of the presented approach is proved by the experiments with a search engine.

Sign-based representation and word model of actor

In this paper a sign-based or semiotic formalism is considered. Neurophysiological and psychological researches indicate sign-based structures, which are the basic elements of the world model of a human subject. These elements are formed during his/her activity and communication. In this formalism it was possible to formulate and solve the problem of goal-setting, i.e. generating the goal of behavior.

Technologies for semantic analysis of scientific publications

The paper presents technologies for semantic analysis of scientific publications. We mainly focus on the stages of natural languages processing and analysis results. The results of experiments with scientific publication examining are presented.

Exactus Like: Plagiarism Detection in Scientific Texts

The paper presents an overview of Exactus Like – a plagiarism detection system. Deep parsing for text alignment helps the system to find moderate forms of disguised plagiarism. The features of the system and its advantages are discussed. We describe the architecture of the system and present its performance.

Signs-Based vs. Symbolic Models

In this paper a sign-based or semiotic formalism is considered. The concept of sign arose in the framework of semiotics. Neurophysiological and psychological researches indicate sign-based structures, which are the basic elements of the world model of a human subject. These elements are formed during his/her activity and communication. In this formalism it was possible to formulate and solve the problem of goal-setting, i.e. generating the goal of behavior.

Information Retrieval for R&D Support

Research and development (R&D) involves not only researchers but also many other specialists from different areas. All of them solve a variety of tasks that require comprehensive information and analytical support. This chapter discusses the major tasks arising in R&D: study of the state of the art in a given research area, prospects assessment of research fields and forecasting their development, quality assessment of scientific publications including plagiarism detection, and automated examination of proposed R&D projects. A number of informational and analytical systems have been developed to address these tasks. The main goal of this chapter is to give a review of R&D support functions of well-known and widely-used search and analytical systems and discuss information retrieval methods behind these functions.

Social Tension Detection and Intention Recognition Using Natural Language Semantic Analysis: On the Material of Russian-Speaking Social Networks and Web Forums

The paper proposes a method of social tension detection and intention recognition based on natural language analysis of social networks, forums, blogs and news comments. Our approach combines natural language syntax and semantics analysis with statistical processing to identify possible indicators of social tension. The universal components of our method incorporate the general laws of natural language, general psychological, sociological and psycholinguistic rules and trends typical of social tension detection in virtual discussions. Automatic monitoring of the contents of discussions helps to timely unveil hidden signs of tension and makes it possible to predict the likely development of the situation.