Models and synthesis method of agent information retrieval system

Main Article Content

Oleg Kasilov
https://orcid.org/0000-0002-8524-2345
Kateryna Kramska
https://orcid.org/0000-0002-9694-0552

Abstract

Existing modern information retrieval systems such as Google, Yandex, Yahoo are aimed at the average user, whose subject of the search is not specific, scientific and technological information. Therefore, the aforecited search systems cannot fully provide the necessary information for the professional user. Due to the fact that this information is reference or encyclopedic which does not correspond to the specified search. It is possible to ensure a high-quality information search and to solve the problem of information and analytical support for scientific and technological activities with the using of agent technologies. Agent technologies are initiated and controlled automatically, and also function without user’s participation, therefore they have higher productivity and the possibility of continuous operation. This article has developed the architecture of a multi-level agent information-analytical system in natural-scientific and technological areas. The authors proposed software and hardware implementations of a thematic service model for collective and personal users. Also, the article discusses the use of agent technologies in information retrieval systems for scientific and technical information. The technique of structural-parametric synthesis of such systems is proposed as well.

Article Details

How to Cite
Kasilov, O., & Kramska, K. (2020). Models and synthesis method of agent information retrieval system. Advanced Information Systems, 4(2), 94–99. https://doi.org/10.20998/2522-9052.2020.2.14
Section
Methods of information systems synthesis
Author Biographies

Oleg Kasilov, National Technical University "Kharkiv Polytechnic Institute", Kharkiv

PhD, Associate Professor, Professor of the Information Systems Department

Kateryna Kramska, National Technical University "Kharkiv Polytechnic Institute", Kharkiv

graduate student of the department “Information Technologies and Systems of Wheel and Track Machines”

References

Aseeva, N.N. and Vanskaya, G.P. (1999), Library and bibliographic classification, Liberia, Moscow.

Jaynarayan, L.H. and Hendler, J. (2000), Control of Agent Based Systems (CoABS) & DARPA Agent Markup Language (DAML), DARPA, Presentation.

Budzko, V.I., Leonov, D.V., Nikolaev, V.S., Onyky, B.N. and Sokolina, K.A. (2011), “The development of information and analytical support for scientific and technical activities at the National Research Nuclear University MEPhI”, High Availability Systems, Vol. 7, No. 4, pp. 4-17.

Manning, D., Raghavan, P. and Schutze, H. (2014), Introduction to the information search, Williams.

Kent, A., Berry, M.M., Luehrs, F.U. and Perry, J.W. (1955), “Machine literature searching VIII. Operational criteria for design-information information retrieval systems”, American documentation, Vol. 6, No. 2, pp. 93-101.

Rijsbergen, C.J. (1979), Information Retrieval, Butterworths, London.

Artamonov, A.A., Ananieva, A.A., Tretyakov, E.S., Kshnyakov, D.O., Onykiy, B.N. and Pronicheva L.V. (2016), “A three-tier model for Structuring of Scuentific and Technical Information”, Journal of Digital Information Management, Vol. 14, No. 3, pp. 184-193.

Roussopoulos, N.D. (1976), A semantic network model of data bases, University of Toronto, Department of Computer Sci-ence, Toronto, Dissertation TR No 104.

Larissa T, Moss and Shaku, Atre (2003), Are Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications, Addison-Wesley Professional.

Ferster, E. and Renz, B. (1983), Methods of correlation and regression analysis, Finance and statistics, Moscow.

Artamonov, A., Ananieva, A., Onykiy, B., Ionkina, K., Galin, I. and Kshnyakiv D. (2016), “Thematic Thesauruses in Agent Technologies for Scientific and Technical Information Search”, Procedia Computer Science, Vol. 88, pp. 493-498.