Article
Full entry |
PDF
(0.5 MB)
Feedback
PDF
(0.5 MB)
Feedback
Keywords:
information retrieval; fuzzy sets; modelling of information systems under indeterminacy; adaptive model
information retrieval; fuzzy sets; modelling of information systems under indeterminacy; adaptive model
Summary:
Information retrieval in information systems (IS) with large amounts of data is not only a matter of an effective IS architecture and design and technical parameters of computer technology used for operation of the IS, but also of an easy and intuitive orientation in a number of offers and information provided by the IS. Such retrievals in IS are, however, frequently carried out with indeterminate information, which requires other models of orientation in the environment of the IS.
References:
[1] Brin, S., Page, L.: The Anatomy of a Large-Scale Hypertextual Web Search Engine. Computer Science Department, Stanford University, Stanford 2001.
[2] Bureš, M., Morávek, A., Jelínek, I.: Nová generace webových technologií. 1.VOX a.s. – Nakladatelství, Praha 2005.
[3] Bureš, J., Procházka, J., Klimeš, C., Walek, B., Pešl, M.: Fuzzy reasoning model for decision making under uncertainty. In: 16th Internat. Conference on Soft Computing Mendel 2010. Brno 2010.
[4] Klimeš, C., Procházka, J.: Reasoning in software support and maintenance. In: Abstracts of Contributions to 5th Internat. Workshop on Data – Algorithm – Decision Making. DAR - UTIA 2009/3, Praha 2009.
[5] Klimeš, C., Procházka, J.: Research paper: Using LFLC for decision making in SW support and maintenance. Research intention DAR – OASA 2/2009, Ostrava, 6 pp.
[6] Novák, V.: Fuzzy množiny a jejich aplikace. SNTL, Praha 1986.
[7] Novák, V.: Fuzzy Relation Equations with Words. Springer, Heidelberg 2004. pp. 167–185. MR 2083023 | Zbl 1066.03038
[8] Novák, V., Perfilieva, I., Močkoř, J.: Mathematical Principles of Fuzzy Logic. Kluwer Academic Publishers, Boston/Dordrecht/London 1999. MR 1733839
Search
Partner of
