Vladimir Zadorozhny

  • Professor

Institution of highest degree:
PhD, Institute for Problems of Informatics, Russian Academy of Sciences, Moscow

Representative Publications

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Karataev, Evgeny and Zadorozhny, Vladimir (2017) Adaptive Social Learning Based on Crowdsourcing. IEEE Transactions on Learning Technologies, 10 (2). 128 - 139. ISSN 1939-1382

Kang, Y and Zadorozhny, V (2016) Process monitoring using maximum sequence divergence. Knowledge and Information Systems, 48 (1). 81 - 109. ISSN 0219-1377

Zadorozhny, Vladimir and Grant, John (2016) A systematic approach to reliability assessment in integrated databases. Journal of Intelligent Information Systems, 46 (3). 409 - 424. ISSN 0925-990

Zadorozhny, Vladimr and Manning, Patrick and Drwenski, Matthew and Karataev, Evgeny (2016) Towards a Social Weather Service: Linking Social Sciences and Information Sciences in Large-Scale Inequality Analysis. Journal of World-Historical Information, 2 (1).

Brusilovsky, P and Somyurek, S and Guerra, J and Hosseini, R and Zadorozhny, V and Durlach, PJ (2016) Open Social Student Modeling for Personalized Learning. IEEE Transactions on Emerging Topics in Computing, 4 (3). 450 - 461.

Kang, Yihuang and Zadorozhny, Vladimir (2016) Process Discovery using Classification Tree Hidden Semi-Markov Model. In: The Fifth IEEE International Workshop on Data Integration and Mining (DIM-2016). In conjunction with IRI'16, 28 July 2016 - 30 July 2016, Pittsburgh, United States of America.

Ren, Yi and Zadorozhny, Vladimir and Oleshchuk , Vladimir and Li, Frank (2012) An Efficient, Robust, and Scalable Trust Management Scheme for Unattended Wireless Sensor Networks. In: 13th International Conference on Mobile Data Management, July 23-26, 2011, Bengaluru, India. (In Press)

Zadorozhny, Vladimir (2012) Large-scale collective intelligence: from in the way to on the way. In: OTS'2012, June 13-14, 2012, Maribor, Slovenia.

Research Interests

Networked information systems, complex adaptive systems, heterogeneous data fusion, wireless and sensor data management, query optimization in distributed environments, scalable architectures for wide-area environments with heterogeneous information servers.