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Usage of graph patterns for concept map extension

References [1] S. Waterhouse The Power of E-learning. The Essential Guide for Teaching in the Digital Age. Allyn& Bacon, 2004, p. 228. [2] J.D. Novak Learning, Creating, and Using Knowledge: Concept Maps as Facilitative Tools in Schools and Corporations . [Kindle e-book], LEA, 2008, Available: Amazon. [3] J. Seale, Using CAA to support student learning , [Online]. Available: http://www.alt.ac.uk/sites/default/files/assets_editor_uploads/documents/ eln004.pdf [Accessed: Oct.1, 2011]. [4

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Impact of Antibody Panel Size on Classification Accuracy

References Witten, I. H., Frank, E. Data Mining: Practical Machine Learning Tools and Techniques, Second Edition. Morgan Kaufmann series in data management systems. San Mateo: Morgan Kaufmann Pub., 2005. 560 p. Quinlan J. R. C4.5: Programs for Machine Learning. San Mateo: Morgan Kaufmann Pub., 1993. 302 p. Holte, R. C. Very simple classification rules perform well on most commonly used datasets. Machine Learning 11-1, 1993, p. 63-90. Kononenko, I

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On Necessity of Semantic Analysis when Evaluating Concept Maps

: Apr. 27, 2017]. [3] A. J. Cañas, L. Bunch, J. D. Novak, and P. Reiska, “Cmapanalysis: an extensible concept map analysis tool,” Journal for Educators, Teachers and Trainers. vol. 4, no. 1 (Special), pp. 36-46, 2013. [4] [4] P. Pirnay-Dummer and D. Ifenthaler, “Automated knowledge visualization and assessment,” in Computer-based diagnostics and systematic analysis of knowledge, D. Ifenthaler, P. Pirnay-Dummer, and N. M. Seel, Eds. New York: Springer, 2010, pp. 77-115. https://doi.org/10.1007/978-1-4419-5662-0_6 [5] M

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State Synchronization Approaches in Web-based Applications

devices” in Proceedings of the 3rd ACM SIGCHI symposium on Engineering interactive computing systems, 2011, pp. 105-110. [5] IETF. (1996, May) Hypertext Transfer Protocol -- HTTP/1.0. [Online]. Available: http://tools.ietf.org/html/rfc1945. [6] Ianixt. (2011, March) Browser Cookie Limits [Online]. Available: http://browsercookielimits.x64.me/ [7] M. Mahemoff, (2010, October) Client-Side Storage - HTML5 Rocks [Online] Available: http://html5rocks.com/en/tutorials/offline/storage/. [8] World Wide Web

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An Extension of BPMN Meta-model for Evaluation of Business Processes

conference on Simulation tools and techniques for communications, networks and systems & workshops (Belgium, 2008), ICST, p. 1-8. Korherr, B., List, B. Extending the EPC and the BPMN with business process goals and performance measures. In Proceedings of the 9th International Conference on Enterprise Information Systems (ICEIS) (3) (2007), J. Cardoso, J. Cordeiro, and J. Filipe, Eds., p. 287-294. Lodhi, A., Köppen, V., Saake, G. Post execution analysis of business processes: Taxonomy and challenges, University of

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Improvement of the Two-Hemisphere Model-Driven Approach for Generation of the UML Class Diagram

“Development of the Tool for Generation of UML Class Diagram from Two-Hemisphere Model.” In: Proceedings of The Third International Conference on Software Engineering Advances (ICSEA), International Workshop on Enterprise Information Systems (ENTISY). Mannaert H., Dini P., Ohta T., Pellerin R. (Eds.), Published by IEEE Computer Society, Conference Proceedings Services (CPS), 2008, pp. 105-112. [6] O. Nikiforova “Two Hemisphere Model Driven Approach for Generation of UML Class Diagram in the Context of MDA”, e- Informatics Software Engineering Journal - Volume

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Code Generation from UML Model: State of the Art and Practical Implications

Unified Software Development Process, Addison-Wesley, 2002, pp. 512. [11] O. Nikiforova, A. Cernickins, and N. Pavlova, “Discussing the Difference between Model-driven Architecture and Model-driven Development in the Context of Supporting Tools,” Proceedings of the 4th International Conference on Software Engineering Advances, IEEE Computer Society, 2009, pp. 1-6. [12] OMG: Catalog of OMG Modeling And Metadata Specifications, [Online]. Available: http://www.omg.org/technology/documents/modeling_spec_catalog.htm [Accessed: Sept. 23, 2012

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Knowledge assessment systems: an overview

] / Bull J., University of Wolverhampton, 2003. - http://asp2.wlv.ac.uk/celt/download.asp?fileid=44&detailsid=200008 Gütl C., Dreher H., Williams R. E-TESTER: a Computer-based Tool for Auto-generated Question and Answer Assessment // Proceedings of ELEARN 2005. - Vancouver, 2005. - P.2929-2936. Aguilar G., Gomez A., Kaijiri K. Learners and Knowledge: A New Personalization Factors Perspective for Adaptive Computer-based Assessment Systems // Proceedings of World Conference on Educational Multimedia, Hypermedia and

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Towards Narrowing a Conceptual Gap between IT Industry and University

References M. Kirikova, J. Grundspenkis, and U. Sukovskis, "Educational "ecosystem" for information systems engineering" in Seventh International Symposium on Tools and Methods of Competitive Engineering , TMCE, April 2008, Turkey. Delft University of Technology, 2008, pp. 769-783. A. R. Hevner, S. T. March, J. Park, and S. Ram, "Design science in information systems research," MIS Quarterly , vol. 28, no. 1, March 2004, pp. 75-105. R. Strazdina and M. Kirikova, "Interaction model

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Time-Series Data Mining for E-Service Application Analysis

References Data Mining: Fundamentals / A. Sukovs L. Aleksejeva K. Makejeva et al. - Riga: Riga Technical University, 2007, p.130. (In Latvian). Thomassey S., Fiordaliso A. A hybrid sales forecasting system based on clustering and decision trees. Decision Support Systems , Volume 42, Issue 1, 2006, p. 408-421. Written I.H., Frank E. Data mining:practical machine learning tools and techniques - 2 nd edition. - Amsterdam etc.: Morgan Kaufman, 2005. Das G

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