Dr. Zdravko Markov

• Buy the book from Wiley (free excerpts available: Chapter 1, TOC, Index) or Amazon.com
• Download data sets: http://www.cs.ccsu.edu/~markov/dmwdata.zip

Spring-2008 Courses

• CS110 - Introduction to Internet Programming and Applications
• CS113 - Introduction to Computers
• CS502 - Computing and Communication Technology
• CS152 - Computer Science II

Previous Courses

• Fall-2007
• CS113 - Introduction to Computers
• CS152 - Computer Science II
• CS354 - Digital Systems Design
• CS580 - Web Mining
• Summer-2007
• CS580 - Data Mining (Vista online course), Syllabus
• CS570 - Machine Learning (Vista online course), Syllabus
• Spring-2007
• CS113 - Introduction to Computers
• CS385 - Computer Architecture
• CS502 - Computing and Communication Technology
• Fall-2006
• CS354 - Digital Systems Design
• CS502 - Computing and Communication Technology
• CS113 - Introduction to Computers (Sections 71, 72)
• Fall-2005, Spring-2006: Sabbatical Leave
• Summer-2005
• CS580 - Topics in Data Bases: Data Mining (graduate course taught online through OnlineCSU)
• Spring-2005
• CS385 - Computer Architecture
• CS462 - Artificial Intelligence
• CS502 - Computing and Communication Technology
• Fall-2004
• CS354 - Digital Systems Design
• CS502 - Computing and Communication Technology
• CS580 - Web Mining
• Summer-2004
• CS580 - Topics in Data Bases: Data Mining (graduate course taught online through OnlineCSU)
• Spring-2004
• CS385 - Computer Architecture
• CS502 - Computing and Communication Technology (graduate course in the CIT program)
• CS570 - Topics in AI: Machine Learning (graduate course taught online through OnlineCSU)
• Fall-2003
• CS213 - Applications of computer programming
• CS502 - Computing and Communication Technology (graduate course in the CIT program)
• CS580 - Tpcs in Data Bases: Data Mining (graduate course in the CIT program)
• Summer-2003
• CS570 - Topics in AI: Machine Learning (graduate course)
• CS580 - Topics in Data Bases: Data Mining (online class available through OnlineCSU)
• Spring-2003
• CS385 - Computer Architecture
• CS502 - Computing and Communication Technology (graduate course in the CIT program)
• CS 580 - Topics in Data Bases: Data Mining (online class taught through OnlineCSU)
• Fall-2002
• CS213 - Applications of computer programming
• CS354 - Digital Systems Design
• CS502 - Computing and Communication Technology (graduate course in the CIT program)
• Summer-2002
• CS580 - Tpcs in Data Bases: Data Mining (graduate course in the CIT program)
• Spring-2002
• CS254 - Computer organization and assembly language programming
• CS385 - Computer Architecture
• CS502 - Computing and Communication Technology (graduate course in the CIT program)
• Fall-2001
• CS502 - Computing and Communication Technology (graduate course in the CIT program)
• CS570 - Topics in AI: Machine Learning (graduate course in the CIT program)
• CS354 - Digital Systems Design
• Summer-2001
• CS580 - Data Mining (graduate course in the CIT program)
• CS580 - Data Mining, online class taught through the OnlineCSU system
• Spring-2001
• CS254 - Computer organization and assembly language programming
• CS385 – Computer Architecture
• CS502 - Computing and Communication Technology (graduate course in the CIT program)
• Fall-2000
• CS254 - Computer organization and assembly language programming
• CS354 - Digital Systems Design
• CS502 - Computing and Communication Technology
• Summer-2000
• CS500 - Computer Science for CIT
• CS580 - Data Mining
• Spring-2000
• CS254 - Computer organization and assembly language programming
• CS385 – Computer Architecture
• CS502 - Computing and Communication Technology
• Fall-1999
• CS254 - Computer organization and assembly language programming
• CS354 - Digital Systems Design
• CS502 - Computing and Communication Technology
• Spring-1999
• CS161 - C programming
• CS213 - Applications of computer programming
• CS385 – Computer Architecture

Research

• Machine Learning
• KDD, Data Mining, Web Mining
• Occam and Bayesian learning
• Instance-based learning
• Conceptual clustering
• Inductive Logic Programming
• Logic Programming and Prolog
• Parallel and distributed implementations of Prolog
• New inference mechanisms
• Prolog extensions

Useful links

1. Machine Learning
• Machine Learning at AAAI
• Journal of Machine Learning Research
• Journal of Machine Learning Gossip (ML humor)
• mdl-research.org
• Machine Learning Database Repository at UC Irvine
• Machine Learning subject index maintained by the Knowledge Systems Laboratory, Canada
• MLnet Online Information Service
• ML Information Services maintained by the Austrian Research Institute for Artificial Intelligence (OFAI)
• David Aha's list of machine learning resources
• Avrim Blum's Machine Learning Page
• The AutoClass Project
• UCI - Machine Learning information, software and databases
• UTCS Machine Learning Research Group
• Microsoft Bayesian Network Editor (MSBNx)
• Machine Learning Journal Online
• Weka 3 -- Machine Learning Software in Java
• Journal of AI Research (online text)
• Journal of Data Mining and Knowledge Discovery
• C5/See5
• MLC++, A Machine Learning Library in C++
• Web->KB project
• DELVE-Data for Evaluating Learning
• Recursive-Partitioning.com
2. Data mining
• Jiawei Han and Micheline Kamber, Data Mining: Concepts and Techniques, Morgan Kaufmann Publishers, 2000
• Data Mining Resources
• The Data Mine, Birmingham, UK.
• Data Miners
• KD Nuggets Directory
• Software for Data Mining / Web Mining
• Journal of Data Mining and Knowledge Discovery
• WinMine Toolkit Home Page
• Knowledge Discovery Central
• KDNet
3. The Web
• The World Wide Web Consortium
• Semantic Web
• International Semantic Web Conference (ISWC)
• The DARPA Agent Markup Language Homepage
• SemanticWeb.org
• The Semantic Web: Scientific American, May 2001.
• Semantic Web History: Nodes and Arcs 1989-1999
• Professor James A. Hendler
4. AI
• AI Overview
• CMU Artificial Intelligence Repository
• Artificial Intelligence: A Modern Approach
5. Other
• The Virtual Library: Computing
• The Alan Turing Home Page
• Ghostscript, Ghostview and GSview
• Postscript to PDF Converter
• The public-domain Prolog library
• Object-Oriented Language: Prolog
• Mathematically Correct
• Information Retrieval Resources and Demos

Talks, tutorials

• Markov, Z., Ingrid Russell, An Introduction to the WEKA Data Mining System, Workshop #5 at The 39th ACM Technical Symposium on Computer Science Education (SIGCSE 2008), Portland, Oregon, March 12-15, 2008. Full text: http://www.cs.ccsu.edu/~markov/weka-tutorial.pdf
• Markov, Z., I. Russell. An Introduction to the WEKA Data Mining System (tutorial), Proceedings of the 11th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education (ITiCSE06), June 26-28, 2006, Bologna, Italy, 367. (Abstract: http://www.cs.ccsu.edu/~markov/iticse-t.pdf, Full text: http://www.cs.ccsu.edu/~markov/weka-tutorial.pdf)
• Markov, Z. An algebraic approach to machine learning and knowledge discovery, Mathematics  Department Colloquium, CCSU, March 2000. (http://www.cs.ccsu.edu/~markov/mathcolloq2000.pdf)

Software

• Zprolog - a DOS window-based Prolog interpreter. Available as a ZIP archive from here.
• Net-Clause Language (NCL) - a language for distributed logic programming based on term unification. Available from the CMU Artificial Intelligence Repository. Also indexed in The public-domain Prolog library.
• Lambda Inductive Logic Programming (LILP) - an ILP algorithm for learning from positive-only examples. Available from here (see the readme.txt file).
• Lambda GENeralization (LGEN) - another algorithm for learning from positive-only examples. Available here (see the readme.txt file).
• Machine Learning Programs and Laboratory Experiments in Prolog. A collection of Prolog programs implementing popular ML algorithms along with Labs. Available here.
• Artificial Intelligence Algorithms in Prolog. A collection of Prolog programs implementing popular AI algorithms. Available here.

Grants, Projects

• 2007-2009: Machine Learning Experiences in Artificial Intelligence: A Multi-Institutional Project, funded by a grant from the National Science Foundation (NSF DUE-0716338)
• 2004-2006: Machine Learning Laboratory Experiences for Introducing Undergraduates to Artificial Intelligence funded by a grant from the National Science Foundation (NSF CCLI-A&I Award Number 0409497)
• 1998-2001. Network of Excellence in Inductive Logic Programming (ILPnet2)
• 1996-1998. TRACE (INCO-COPERNICUS Project No. 96-0138)
• 1991-1998. ESPRIT Network of Excellence in Computational Logic (COMPULOG)
• 1995-1997. ESPRIT Network of Excellence in Machine Learning (MLnet)
• 1993-1996. PECO Pan-European Scientific Network on Inductive Logic Programming (ILPNET)

Program Committees, Conferences

• Associate Editor, International Journal on Artificial Intelligence Tools (IJAIT)
• PC member, 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI-07)
• Co-chair of the Special Track on Machine Learning at  FLAIRS-2007
• Co-chair of the Special Track on Machine Learning at  FLAIRS-2006
• Program co-chair of  The 18th International FLAIRS Conference (FLAIRS-2005)
• Co-chair of the Special Track on Machine Learning at  FLAIRS-2005
• Program co-chair of  The 17th International FLAIRS Conference (FLAIRS-2004)
• Co-chair of the Special Track on Machine Learning, The 17th International FLAIRS Conference (FLAIRS-2004)
• Chair of the Special Track on Machine Learning, The 16th International FLAIRS Conference (FLAIRS-2003)
• Chair of the Special Track on Machine Learning, The 15th International FLAIRS Conference (FLAIRS-2002)
• Chair of the Special Track on Machine Learning, The 14th International FLAIRS Conference (FLAIRS-2001)
• PC member of AIMSA'98 Conference

Degrees and academic experience

• Ph.D. in AI (1991) from Sofia University
• B.S. in Mathematics (1979) and M.S. in Computer Science (1981) from Sofia University

• Department of Computer Science, Central Connecticut State University
• Department of Information Technology, Faculty of Mathematics & Informatics, Sofia University
• Institute of Information Technologies, Bulgarian Academy of Sciences

Bibliography

Books:

• Zdravko Markov and Daniel Larose, Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage, Wiley, April 2007.
• Dochev, D., Ch. Dichev, Z. Markov, G. Agre. Programming in Prolog - principles and applications, Nauka i Iskustvo, Sofia, 1989 (in Bulgarian).
• Markov, Z. Inductive Methods for Machine Learning, TEMPUS JEN 1497 & SOFTEX, 1996 (in Bulgarian).
• Agre, G., Markov, Z., Dochev, D. Introduction to Machine Learning, TEMPUS JEN 1497 & SOFTEX, 2001 (in Bulgarian).

• Wallace, S., Ingrid Russell, and Zdravko Markov, Integrating Games and Machine Learning in the Undergraduate Computer Science Classroom, Microsoft Academic Days on Game Development in Computer Science Education (GDCSE'08), Aboard the Celebrity Century Cruise Ship, February 28 - March 3, 2008. (http://www.cs.ccsu.edu/~markov/papers/gdcse08.pdf)
• Neller T., Ingrid Russell, and Zdravko Markov, Throw Down an AI Challenge, Using AI to motivate greater participation in Computer Science, AAAI Spring Symposium, Stanford University, March 26 - 28, 2008. (http://www.cs.ccsu.edu/~markov/papers/aaaiss08.pdf)
• Holder, L., Z. Markov and I. Russell. Advances in Knowledge Acquisition and Representation, International Journal on Artificial Intelligence Tools (IJAIT), Vol. 15, No. 6 (2006) 867-874. (http://www.cs.ccsu.edu/~markov/papers/ijait06.pdf)
• Russell, I.,  Z. Markov and L. Holder (Guest Editors). Special Issue on FLAIRS 2005: Knowledge Acquisition and Representation, International Journal of Artificial Intelligence Tools (IJAIT), Vol. 15, No. 6 (December 2006).
• Neller T., Clifton G.M. Presser, Ingrid Russell, Zdravko Markov. Pedagogical Possibilities for the Dice Game Pig, Journal of Computing Sciences in Colleges, Vol. 21, no. 6, pp. 149-161, June 2006. (http://cs.gettysburg.edu/~tneller/papers/ccscne06.pdf)
• Markov, Z., I. Russell, T. Neller, N. Zlatareva. Pedagogical Possibilities for the N-Puzzle Problem, Proceedings of the 36th Annual Frontiers in Education Conference (FIE 2006), San Diego, California, October 28 - 31, 2006. (http://www.cs.ccsu.edu/~markov/fie06.pdf)
• Russell, I., Z. Markov, T. Neller. Teaching Al through Machine Learning Projects, Proceedings of the 11th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education (ITiCSE06), June 26-28, 2006, Bologna, Italy, 323. (http://www.cs.ccsu.edu/~markov/iticse-p.pdf)
• Neller T., Zdravko Markov, Ingrid Russel. Clue Deduction: Professor Plum Teaches Logic, Proceedings of the 19th International FLAIRS Conference (FLAIRS-2006), Melbourne Beach, Florida, May 11-13, 2006, 214-219. (http://cs.gettysburg.edu/~tneller/papers/flairs06.pdf)
• Ingrid Russell, Zdravko Markov, Lawrence B. Holder, Diane Cook: The 2005 International Florida Artificial Intelligence Research Society Conference: A Report. AI Magazine 27(1): 109-113 (2006).
• Markov, Z., I. Russell, T. Neller, and S. Coleman. “Enhancing Undergraduate AI Courses through Machine Learning Projects”, Proceedings of the 35th ASEE/IEEE Frontiers in Education Conference, October 2005, Indianapolis, IN. (http://cs.gettysburg.edu/~tneller/papers/fie05.pdf)
• Russell, I., Z. Markov, T. Neller, M. Georgiopoulos and S. Coleman. Unifying an Introduction to Artificial Intelligence Course through Machine Learning Laboratory Experiences, Proceedings of the 25th American Society for Engineering Education Annual Conference and Exposition, Portland, Oregon, June 12-15, 2005, ASEE Press. (http://cs.gettysburg.edu/~tneller/papers/asee05.pdf)
• Ingrid Russell, Zdravko Markov (Editors): Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, Clearwater Beach, Florida, USA, AAAI Press 2005.
• Ingrid Russell, Zdravko Markov, Brian Carse, Anthony G. Pipe, Lawrence B. Holder (Editorial). International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), Vol. 19(2): 129-132 (2005).
• Lawrence B. Holder, Ingrid Russell, Zdravko Markov, Anthony G. Pipe, Brian Carse. Current And Future Trends In Feature Selection And Extraction For Classification Problems, International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), Vol. 19(2): 133-142 (2005). (http://www.cs.ccsu.edu/~markov/ijprai05.pdf
• Zdravko Markov, Valerie Barr (Guest Editors). Special Issue on Selected Papers from the 17-th International FLAIRS Conference (FLAIRS-2004), International Journal of Artificial Intelligence Tools (IJAIT), Vol. 14, No. 1 & 2, February & April 2005.
• Valerie Barr, Zdravko Markov (Editors). Proceedings of the 17th International Florida Artificial Intelligence Research Symposium Conference (FLAIRS-2004), Miami Beach, Florida, AAAI Press 2004.
• Russell, I., Z. Markov and N. Zlatareva. Introducing Machine Learning from an AI Perspective, Proceedings of the 13^th International Conference on Artificial Neural Networks and Neural Information Processing (ICANN/ICONIP 2003), 469-473. (http://www.cs.ccsu.edu/~markov/icann03.pdf)
• Boytcheva, S and Z. Markov. An algorithm for inducing least generalization under relative implication, in: Proceedings of FLAIRS-2002, Pensacola, Florida, May 14-16, 2002, AAAI Press, 2002, 322-326 (http://www.cs.ccsu.edu/~markov/flairs2002.pdf).
• Markov, Z. An algebraic approach to inductive learning, the International Journal of Artificial Intelligence Tools (IJAIT), Vol. 10, No.1-2 (2001), 257-272. (http://www.cs.ccsu.edu/~markov/ijait01.pdf)
• Markov, Z. A lattice-based approach to hierarchical clustering, in: Proceedings of FLAIRS-2001, Key West, Florida, May 21-23, 2001, AAAI Press, 2001, 389-393 (http://www.cs.ccsu.edu/~markov/flairs2001.pdf).
• Markov, Z. and I. Marinchev. Coverage-based semi-distance between Horn clauses, in: S. Cerri and D. Dochev (eds.),  Proceedings of AIMSA'2000, Lecture Notes in Computer Science, Vol. 1904, Springer 2000, 331-339 (http://www.cs.ccsu.edu/~markov/aimsa2000.pdf).
• Markov, Z. and I. Marinchev. Metric-based inductive learning using semantic height functions, in: Ramon López de Mántaras, Enric Plaza (eds.), Proceedings of ECML-2000, Lecture Notes in Computer Science, Vol. 1810, Springer, 2000, 254-262 (http://www.cs.ccsu.edu/~markov/ecml2000.pdf).
• Markov, Z. An algebraic approach to inductive learning, in: Proceedings of FLAIRS-2000, AAAI Press, 2000, 197-201 (http://www.cs.ccsu.edu/~markov/flairs2000.pdf).Markov, Z. Generalization under Implication by lambda-Subsumption, in: David Page (ed.), Proceedings of the 8th International Workshop on Inductive Logic Programming (ILP-98), Madison, Wisconsin, USA, July 22-24, 1998, Lecture Notes in Computer Science, Vol. 1446, Springer, 1998, 215-224.
• Agre, G., Ch. Dichev, Z. Markov. Task Editor - A Knowledge Acquisition Tool for Task Analysis, in: P. Navrat, H. Ueno (Eds.), Knowledge-Based Software Engineering, IOS Press, 1998, 191-194.
• Markov, Z. and N. Pelov. A framework for Inductive Learning Based on Subsumption Lattices, in: F. Guinchiglia (ed.), Proceedings of AIMSA'98,  Lecture Notes in Artificial Intelligence, Vol.1480, Springer, 1998, 341-352.
• Markov, Z. Lambda-Subsumption and Its Application to Learning from Positive-only Examples, in: S. Muggleton (ed.), Proceedings of the 6th International Workshop on Inductive Logic Programming (ILP-96), Stockholm, August, 1996, Selected Papers, Lecture Notes in Artificial Intelligence, Vol.1314, Springer, 1997, 377-396.
• Markov, Z. A Model-theoretic Approach to ILP for Learning from Positive-only Examples, in: A. Ramsay (ed.), Artificial Intelligence: Methodology, Systems, Applications, IOS Press, 1996, 41-50.
• Markov, Z. Inductive Logic Programming, Problems of Engineering  Cybernetic  and  Robotics,  Vol.42,  Bulgarian Academy  of  Sciences, 1995, 56-65.
• Markov, Z. A Functional Approach to ILP, in: Luc De Raedt (ed.), Proceedings of the 5th International Workshop in Inductive Logic Programming (ILP-95), Scientific report, Department of Computer Science, K.U. Leuven, September, 1995, 267-280.
• Markov, Z. and L. Sinapova. A Framework for Network Modeling, Computers and Artificial Intelligence, Vol.13 (1994), No.6, Bratislava, 577-593.
• Markov, Z. Dynamic Induction in Network of Relations, in: Ph. Jorrand and V. Sgurev (Eds.), Proceedings of AIMSA'94, World Scientific, 1994, 239-246.
• Markov, Z. Relational Learning by Heuristic Evaluation of Ground Data, in: S. Wrobel (Ed.), Proceedings of Fourth International Workshop on Inductive Logic Programming (ILP-94), September 12- 14, 1994, Bad Honnef/Bon, Germany, GMD-Studien Nr.237, 337-349.
• Markov, Z. Inductive Inference in Networks of Relations, in: Proceedings of the Third International Workshop on Inductive Logic Programming (ILP-93), April 1-3, Bled, Slovenia, 256-277.
• Sinapova, L. and Z. Markov. Grammar Representation and Parsing in a Data-Driven Logic Programming Environment, in: Proceedings of AIMSA'92,  Artificial Intelligence V, North-Holland, 151-159.
• Markov, Z. An approach to Concept Learning Based on Term Generalization, in: Proceeding of the 9th International Machine Learning Conference (ML92), Aberdeen, Scotland, 1-3 July, Morgan Kaufman, San Mateo CA, 1992, 310-315.
• Markov, Z. A tool for building connectionist-like networks based on term unification, in: M. Richter and H. Boley (eds.), Proceedings of PDK'91, Lecture Notes in Computer Science, Vol.567, Springer-Verlag, 1991, 119-203.
• Markov, Z. and Ch. Dichev. Distributed Logic Programming, in: G. Wiggins, C. Mellish and T. Duncan (eds.), Proceedings of the 3rd UK Annual Conference of Logic Programming, Edinburgh, Scotland, 1991 (Workshops in Computing, Springer-Verlag, 1991, 36-55).
• Markov, Z. An Approach to Data-Driven Learning, in: Proceedings of the International Workshop on Fundamentals of Artificial Intelligence Research (FAIR'91), September 8-12, 1991, Smolenice, Czechoslovakia, Lecture Notes in Computer Science, Vol.535, Springer-Verlag, 1991, 127-140.
• Sgurev V., D. Dochev, G. Agre, Ch. Dichev, Z.  Markov.  Diagnostic Expert Systems For Digital Electronics, in: Proceedings of the IFIP TC5/WG5.3 International Conference on Artificial  Intelligence in CIM, Leningrad,  April 1990, North-Holland, 1991, 220-224.
• Markov, Z. and Ch. Dichev. The Net-Clause Language - A Tool for Data-Driven Inference, in: Logics in AI, Proceedings of European Workshop JELIA'90, Amsterdam, The Netherlands, September 1990, Lecture Notes in Computer Science, Vol.478, Springer-Verlag, 1991, 366-385.
• Markov, Z., L. Sinapova and Ch. Dichev. Default reasoning in a network environment, in: Proceedings of the 9th European Conference on Artificial Intelligence (ECAI-90), August 6-10,1990, Stockholm, Sweden, 431-436.
• Markov, Z., C. Dichev and L. Sinapova. The Net-Clause Language - a tool for describing network models, in: Proceedings of the Eighth Canadian Conference on AI (CSCSI-90), 23-25 May, 1990, Ottawa, Canada, 33-39.
• Markov, Z. A Framework for Network Modeling in Prolog, in: Proceedings of IJCAI-89, Detroit, U.S.A, August 20-25, Morgan Kaufmann, 1989, 78-83.
• Dichev,  Ch.,  G. Agre, D. Dochev, Z. Markov. Trigonometry Tutor, in: Proceedings of the Fourth International Annual PEG Conference "Learning with Artificial Intelligence". Uppsala, Sweden, June 16-18, 1989.
• Markov Z., Th. Risse. Prolog Based Graph Representation of Polyhedra, in: Proceedings  of  AIMSA'88, North-Holland, 1988, 187-194.
• Sgurev, V., D. Dochev,  Z.  Markov,  Ch. Dichev,  G. Agre. Knowledge  representation  in  CAD, in: I. Plander (ed.), Artificial  Intelligence and Information-Control  Systems  of  Robots-87, North-Holland, 1987, 99-106.
• Sgurev, V., D. Dochev,  G. Agre,  Ch. Dichev,  Z.  Markov.  Knowledge  Acquisition  and Man-Machine Interface in the DIGS Expert System, in: Proceedings of AIMSA'86, North-Holland, 1987, 281-288.
• Markov, Z., D. Dochev,  Ch. Dichev,  G. Agre. An Approach to Compiling  Prolog Programs,  in: Proceedings of AIMSA'86,  North-Holland, 1987, 47-54.
• Messina, L.A.,  Z. Markov. Methodisches Evaluieren von CAD- Systemen, Aktuelle Themen der Graphischen Datenverarbeitung, J.Enacarnacao (Hrsg.). Springer-Verlag 1986, 277-294.
• Hubner, W., Z.  Markov. GKS Based Graphics Programming in PROLOG. Computer Graphics Forum, Vol.5, No.1. North-Holland, March 1986.
• Sgurev, V., D. Dochev, Ch. Dichev, G. Agre, Z. Markov. An approach  to  building  a technical diagnostic expert system. Computers and Artificial Intelligence,  Vol.5(1986), No.2, Bratislava, 103-115.
• Agre, G., V. Sgurev, D. Dochev, Ch. Dichev, Z. Markov. An implementation of the expert system DIGS for diagnostics, Computers and  Artificial  Intelligence, Vol.4(1985), No.6, Bratislava, 495-502.
• Encarnacao,  J., L.A.Messina, Z. Markov. Models and Methods for Decision Support Systems for Evaluating  and Choosing  CAD-Systems, in: Preprints  of  IFIP  W.G.5.2 Working Conference on Design Theory for CAD, Tokyo, October 1-3, 1985, 213-230.
• Hubner, W., Z. Markov. Eine Graphik-Erweiterung fur PROLOG auf der Grundlage von GKS, in: GI, OCG, OGI JAHRESTAGUNG 1985, September, 1985, Wien, 16-20.
• Sgurev, V., D. Dochev, Ch. Dichev, G. Agre, Z. Markov. A Domain Independent Expert System for Technical Diagnostics,  in: Proceedings of AIMSA'84, North-Holland, 1985, 137-144.