Abstract
In terms of search procedures and problem-oriented knowledge processing, complexity of identification and usage of key information is increasing constantly. A suggested hypothesis is based on the following statement: one of the ways to solve this problem is the improvement of semantic models for interpretation and using metadata of already-existing search profiles, pursuing similar aims, as prior data. We researched case-based reasoning in semantic search relating to knowledge filter. Concrete scientific results are: agent model, metamodel and case-model of knowledge filter which can solve problems of semantic identification of key information and processing of heterogeneous knowledge resources on the basis of ontology-based structures.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Amerland, D.: Google Semantic Search: Search Engine Optimization (SEO) Techniques That Gets Your Company More Traffic, Increases Brand Impact and Amplifies Your Online Presence. D.Amerland. Que Publishing, 230 p (2013)
Bova, V.V., Kravchenko, Y.A., Kureichik, V.V.: Decision support systems for knowledge management. Software Engineering in Intelligent Systems. In: Proceedings of the 4th Computer Science On-line Conference 2015 (CSOC2015), vol. 3, pp. 123–130. Springer International Publishing AG, Switzerland (2015)
Bova, V.V., Kravchenko, Y.A., Kureichik, V.V.: Development of distributed information systems: ontological approach. Software Engineering in Intelligent Systems. In: Proceedings of the 4th Computer Science On-line Conference 2015 (CSOC2015), vol. 3, pp 113–122. Springer International Publishing AG, Switzerland (2015)
Eberhart, R.C., Shi, Y.: Particle swarm optimization: developments, applications and resources. In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Seoul, Korea (2001)
Gangeni, A.: An Overview of the ONIONS Project: Applying Ontologies to the Integration of Medical Terminologies. In: Gangeni, A., Pisanelli, D.M., Steve, G. (eds.) Data and Knowledge Engineering, vol. 31. pp. 183–220 (1999)
He, Q., Zhao, X.R., Luo, P., Shi, Z.Z.: Combination methodologies of multi-agent hyper surface classifiers: design and implementation issues Second international workshop. AIS-ADM 2007. Proceedings, pp. 100–113. Springer, Berlin, Heidelberg, (2007)
Hu, X., Shi, Y., Eberhart, R.C.: Recent Advances in Particle Swarm. In: Proceedings of Congress on evolutionary Computation (CEC), Portland, Oregon, pp. 90–97 (2004)
Kerschberg, L., Jeong, H., Kim, W.: Emergent Semantic in Knowledge Sifter: An Evolutionary Search Agent based on Semantic Web Services. In: Spaccapietra, S., Aberer, K., Cudre-Mauroux, P. (eds.) Journal on Data Semantic VI. LNCS, vol. 4090, pp. 187–209. Springer, Heidelberg (2006)
Kravchenko, Y.A., Kureichik, V.V.: Knowledge management based on multi-agent simulation in informational systems. Conference proceedings. In: 8th IEEE International Conference “Application of Information and Communication Technologies, AICT 2014”, pp 264–26715–17 Oct 2014, Astana, Kazakhstan
Shi, Y., Eberhart, R.C.: A modified particle swarm optimizer. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pp. 69–73. Piscataway, NJ (1998)
Sousa, T., Silva, A., Neves, A.: Particle Swarm based Data Mining Algorithms for classification tasks. Parallel Comput. 30(5–6), 767–783 (2004)
Acknowledgments
The study was performed by the grant from the Russian Science Foundation (project # 14-11-00242) in the Southern Federal University.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Kravchenko, Y., Kursitys, I., Bova, V. (2016). Models for Supporting of Problem-Oriented Knowledge Search and Processing. In: Abraham, A., Kovalev, S., Tarassov, V., Snášel, V. (eds) Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’16). Advances in Intelligent Systems and Computing, vol 450. Springer, Cham. https://doi.org/10.1007/978-3-319-33609-1_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-33609-1_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-33608-4
Online ISBN: 978-3-319-33609-1
eBook Packages: EngineeringEngineering (R0)