Selected Publications (over 100 publications before 1996 are not included)

	Principles of Data Mining (fourth edition) Published by Springer-Verlag, 2020. Explains and explores the principal techniques of Data Mining: for classification, generation of association rules and clustering.
	Web Programming With PHP and MySQL (first edition) Published by Springer-Verlag, 2015. Covers all the main features of the 'web programming' languages PHP and MySQL
	Logic Programming With Prolog (second edition) Published by Springer-Verlag, 2013. Teaches the techniques of Logic Programming through the Prolog language.
	Knowledge Discovery and Data Mining Published by the IEE in the Professional Applications of Computing series. An edited collection of refereed papers covering both theory and practice in this important field.
	Artificial Intelligence: An International Perspective Published by Springer in the LNAI Series 2009. Comprises chapters on new or emerging areas of Artificial Intelligence contributed by expert members of IFIP Technical Committee 12, its Working Groups and their colleagues. Online version

1. M.A.Bramer and F.Stahl (eds.) (2023)
   Artificial Intelligence XL
   Springer Lecture Notes in Artificial Intelligence Vol. 14381. ISBN: 978-3-031-47993-9
2. M.A.Bramer and F.Stahl (eds.) (2022)
   Artificial Intelligence XXXIX
   Springer Lecture Notes in Artificial Intelligence Vol. 13652. ISBN: 978-3-031-21441-7
3. Manal Almutairi, Frederic Stahl and Max Bramer (2022)
   CRC: Consolidated Rules Construction for Expressive Ensemble Classification
   In: Artificial Intelligence XXXIX, Springer Lecture Notes in Artificial Intelligence, Vol. 13652, pp.138-152.
4. M.A.Bramer and R.Ellis (eds.) (2021)
   Artificial Intelligence XXXVIII
   Springer Lecture Notes in Artificial Intelligence Vol. 13101. ISBN: 978-3-030-91100-3
5. M. Almutairi, F. Stahl and M. Bramer (2021)
   ReG-Rules: An Explainable Rule-Based Ensemble Learner for Classification
   IEEE Access, vol. 9, pp. 52015-52035, 2021, doi: 10.1109/ACCESS.2021.3062763.
6. M.A.Bramer and R.Ellis (eds.) (2020)
   Artificial Intelligence XXXVII
   Springer Lecture Notes in Artificial Intelligence Vol. 12498. ISBN: 978-3-030-63798-9
7. Max Bramer (2020)
   Principles of Data Mining (fourth edition)
   Springer-Verlag. ISBN: 978-1-4471-7492-9
8. M.A.Bramer and M.Petridis (eds.) (2019)
   Artificial Intelligence XXXVI
   Springer Lecture Notes in Artificial Intelligence Vol. 11311. ISBN: 978-3-030-34884-7
9. M.A.Bramer and M.Petridis (eds.) (2018)
   Artificial Intelligence XXXV
   Springer Lecture Notes in Artificial Intelligence Vol. 11311. ISBN: 978-3-030-04190-8
10. M.A.Bramer and M.Petridis (eds.) (2017)
    Artificial Intelligence XXXIV
    Springer Lecture Notes in Artificial Intelligence Vol. 10630. ISBN: 978-3-319-71078-5
11. M.Almutairi, F.Stahl and M.Bramer (2017)
    Improving Modular Classification Rule Induction with G-Prism Using Dynamic Rule Term Boundaries
    In: Artificial Intelligence XXXIV, Springer Lecture Notes in Artificial Intelligence, Vol. 10630, pp.115-128. ISBN: 978-3-319-71078-5
12. M.A.Bramer and M.Petridis (eds.) (2016)
    Research and Development in Intelligent Systems XXXIII
    Springer-Verlag. ISBN: 978-3-319-47174-7 (Print) 978-3-319-47175-4 (eBook)
13. M.Almutairi, F.Stahl. M.Jennings, T.Le and M.Bramer (2016)
    Towards Expressive Modular Rule Induction for Numerical Attributes
    In: Research and Development in Intelligent Systems XXXIII, Springer-Verlag, pp.229-235. ISBN 978-3-319-47174-7
14. Max Bramer (2016)
    Principles of Data Mining (third edition)
    Springer-Verlag. ISBN: 978-1-4471-7306-9 (Print) 978-1-4471-7307-6 (eBook)
15. M.A.Bramer (2015)
    Web Programming with PHP and MySQL (first edition)
    Springer 2015. ISBN: 978-3-319-22658-3
16. M.A.Bramer and M.Petridis (eds.) (2015)
    Research and Development in Intelligent Systems XXXII
    Springer-Verlag. ISBN: 978-3-319-25030-4 (Print) 978-3-319-25032-8 (eBook)
17. F.Stahl, D.May, H.Mills, M.Bramer and M.M.Gaber (2015)
    A Scalable Expressive Ensemble Learning using Random Prism: A MapReduce Approach
    Transactions on large-scale data and knowledge-centered systems, Springer, 9070, pp. 90-107. ISBN: 978-3-662-46702-2. DOI 10.1007/978-3-662-46703-9_4.
18. M.A.Bramer and M.Petridis (eds.) (2014)
    Research and Development in Intelligent Systems XXXI
    Springer-Verlag. ISBN: 978-3-319-12068-3 (Print) 978-3-319-12069-0 (eBook)
19. F.Stahl and M.Bramer (2014)
    Random Prism: a noise tolerant alternative to Random Forests
    Expert Systems, Wiley, 31(5), pp. 411-420. ISSN: 1468-0394. doi: 10.1111/exsy.12032.
20. Max Bramer (2013)
    Logic Programming with Prolog (second edition)
    Springer-Verlag. ISBN: 978-1-4471-5486-0 (Print) 978-1-4471-5487-7 (Online)
21. M.A.Bramer and M.Petridis (eds.) (2013)
    Research and Development in Intelligent Systems XXX
    Springer-Verlag. ISBN: 978-3-319-02620-6 (Print) 978-3-319-02621-3 (Online)
22. Max Bramer (2013)
    Principles of Data Mining (second edition)
    Springer-Verlag. ISBN: 978-1-4471-4883-8 (Print) 978-1-4471-4884-5 (Online)
23. F.Stahl, M.M.Gaber and M.Bramer (2013)
    Scaling up Data Mining Techniques to Large Datasets Using Parallel and Distributed Processing.
    In: Rausch, P. Sheta, A. F. and Ayesh, A. (eds.) Business Intelligence and Performance Management. Advanced Information and Knowledge Processing. Springer London, pp. 243-259. ISBN: 978-1-4471-4865-4. doi: 10.1007/978-1-4471-4866-1_16
24. M.A.Bramer and M.Petridis (eds.) (2012)
    Research and Development in Intelligent Systems XXIX
    Springer-Verlag. ISBN 978-1-4471-4738-1
25. F.Stahl, D.May and M.Bramer (2012)
    Parallel Random Prism: A Computationally Efficient Ensemble Learner for Classification
    In: Research and Development in Intelligent Systems XXIX, Springer-Verlag, pp.21-34. ISBN 978-1-4471-4738-1
26. F.Stahl and M.Bramer (2012).
    Computationally Efficient Induction of Classification Rules with the PMCRI and J-PMCRI Frameworks
    Knowledge Based Systems. Elsevier, 35, pp.49-63. ISSN 0950-7051.
27. F. Stahl, M. Gaber, P. Aldridge, D. May, H. Liu, M. Bramer and P. Yu (2012)
    Homogeneous and Heterogeneous Distributed Classification for Pocket Data Mining
    In A. Hameurlain, J.Kung and R.Wagner (eds.), Transactions on Large-Scale Data- and Knowledge-Centered Systems, Lecture Notes in Computer Science 7100, Springer-Verlag, Volume 5, pp.183-205. ISBN 978-3-6422-8147-1
28. M.A.Bramer, M.Petridis and L.Nolle (eds.) (2011)
    Research and Development in Intelligent Systems XXVIII
    Springer-Verlag. ISBN 978-1-4471-2317-0
29. F.Stahl and M.Bramer (2011)
    Random Prism: An Alternative to Random Forests
    In: Research and Development in Intelligent Systems XXVIII, Springer-Verlag, pp.5-18. ISBN 978-1-4471-2317-0
30. F.Stahl and M.Bramer (2012)
    Jmax-pruning: A facility for the information theoretic pruning of modular classification rules
    Knowledge Based Systems, Elsevier, Volume 29, pp.12-19. ISSN 0950-7051
31. M.A.Bramer (ed.) (2012)
    Special Issue of Knowledge Based Systems Journal
    Vol.29, 2012. Elsevier. ISSN 0950-7051
32. F.Stahl and M.Bramer (2012)
    Scaling Up Classification Rule Induction Through Parallel Processing
    Knowledge Engineering Review, Cambridge Journals. ISSN: 1469-8005. doi: 10.1017/S0269888912000355
33. F.Stahl F, M.Gaber, M.Bramer and P.S. Yu (2011)
    Distributed Hoeffding Trees for Pocket Data Mining
    Proceedings of the 2011 International Conference on High Performance Computing & Simulation (HPCS 2011), Special Session on High Performance Parallel and Distributed Data Mining (HPPD-DM 2011), Istanbul, Turkey, IEEE press, pp.686-692. ISBN 978-1-6128-4380-3.
34. F.Stahl F, M.Gaber, H.Liu, M.Bramer and P.S. Yu (2011)
    Distributed Classification for Pocket Data Mining
    Proceedings of the 19th International Symposium on Methodologies for Intelligent Systems (ISMIS 2011), Warsaw, Poland. Lecture Notes in Computer Science LNCS 6804, Springer Verlag, pp.336-345. ISBN 978-3-642-21915-3.
35. M.A.Bramer, M.Petridis and A.Hopgood (eds.) (2011)
    Research and Development in Intelligent Systems XXVII
    Springer-Verlag. ISBN 978-0-85729-129-5
36. F.Stahl and M.Bramer (2011)
    Induction of Modular Classification Rules: Using Jmax-pruning
    In: Research and Development in Intelligent Systems XXVII, Springer-Verlag, pp.79-92. ISBN 978-0-85729-129-5
37. F.Stahl, M.Gaber, M.Bramer and P.S.Yu (2010)
    Pocket Data Mining: Towards Collaborative Data Mining in Mobile Computing Environments
    Proceedings of the IEEE Twenty-second International Conference on Tools with Artificial Intelligence (ICTAI 2010), Arras, France, pp.323-330. ISBN 978-1-4244-8817-9
38. M.A.Bramer (ed.) (2010)
    Artificial Intelligence in Theory and Practice III
    Springer. ISBN 978-3-642-15285-6
39. F.T.Stahl, M.A.Bramer and M.Adda (2010)
    J-PMCRI: A Methodology for Inducing Pre-pruned Modular Classification Rules
    In: Artificial Intelligence in Theory and Practice III, Springer, pp. 47-56. ISBN 978-3-642-15285-6
40. M.A.Bramer (ed.) (2010)
    Special Issue of Knowledge Based Systems Journal
    Vol.23, Issue 4. May 2010. Elsevier. ISSN 0950-7051
41. M.A.Bramer, R.Ellis and M.Petridis (eds.) (2010)
    Research and Development in Intelligent Systems XXVI
    Springer-Verlag. ISBN 978-1-84882-982-4
42. F.Stahl, M.Bramer and M.Adda (2010)
    Parallel Rule Induction with Information Theoretic Pre-Pruning
    In: Research and Development in Intelligent Systems XXVI, Springer-Verlag, pp.151-164. ISBN 978-1-84882-982-4
43. F.Stahl, M.Bramer and M.Adda (2009)
    PMCRI: A Parallel Modular Classification Rule Induction Framework
    In: P. Perner (Ed.), Machine Learning and Data Mining in Pattern Recognition, LNAI 5632, Springer Verlag Heidelberg, p. 148-162. ISBN: 978-3-642-03069-7
44. M.A.Bramer (ed.) (2009)
    Artificial Intelligence: An International Perspective
    Springer Lecture Notes in Artificial Intelligence (LNAI 5640). ISBN 978-3-642-03225-7. ISSN 0302-9743.
45. H.Benbrahim and M.Bramer (2009)
    Text and Hypertext Categorization
    In: Artificial Intelligence: An International Perspective. Springer Lecture Notes in Artificial Intelligence (LNAI 5640). ISBN 978-3-642-03225-7. ISSN 0302-9743.
46. M.A.Bramer (ed.) (2009)
    Special Issue of Knowledge Based Systems Journal
    Vol.22, Issue 7. October 2009. Elsevier. ISSN 0950-7051
47. L.Iliadis, I.Vlahavas and M.A.Bramer (eds.) (2009)
    Artificial Intelligence Applications and Innovations III
    Springer. ISBN 978-1-4419-0220-7
48. M.A.Bramer (ed.) (2009)
    Special Issue of the International Journal of Applied Intelligence on 'Emerging Artificial Intelligence Applications and Innovations'
    Springer.Vol. 30, No.1, February 2009, pp. 1-71. ISSN: 0924-669X
49. M.A.Bramer, F.Coenen and M.Petridis (eds.) (2009)
    Research and Development in Intelligent Systems XXV
    Springer-Verlag. ISBN 978-1-84882-170-5
50. F.T.Stahl, M.A.Bramer and M.Adda (2008)
    Parallel Induction of Modular Classification Rules
    In: Research and Development in Intelligent Systems XXV, Springer. ISBN 978-1-8488-2170-5
51. M.A.Bramer (ed.) (2008)
    Artificial Intelligence in Theory and Practice II
    Springer Science+Business Media. ISBN 978-0-387-09694-0
52. F.T.Stahl, M.A.Bramer and M.Adda (2008)
    P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
    In: Artificial Intelligence in Theory and Practice II, Springer, pp. 77-86. ISBN 978-0-387-09694-0
53. H.Benbrahim and M.A.Bramer (2008)
    A Fuzzy Semi-Supervised Support Vector Machines Approach to Hypertext Categorization
    In: Artificial Intelligence in Theory and Practice II, Springer, pp. 97-106. ISBN 978-0-387-09694-0
54. M.A.Bramer (ed.) (2008)
    Special Issue of Knowledge Based Systems Journal
    Vol. 21, No.3. April 2008. Elsevier. ISSN 0950-7051
55. M.A.Bramer, F.Coenen and M.Petridis (eds.) (2008)
    Research and Development in Intelligent Systems XXIV
    Springer-Verlag. ISBN 978-1-84800-093-3
56. F.Stahl and M.A.Bramer (2007)
    Towards a Computationally Efficient Approach to Modular Classification Rule Induction
    In: Research and Development in Intelligent Systems XXIV, Springer-Verlag, pp. 357-362. ISBN 978-1-84800-093-3.
57. M.A.Bramer (ed.) (2007)
    Special Issue of Knowledge Based Systems Journal
    Vol. 20, No.2. March 2007. Elsevier. ISSN 0950-7051
58. M.A.Bramer (2007)
    Principles of Data Mining
    Springer-Verlag. ISBN: 978-1-84628-765-7.
59. M.A.Bramer, F.Coenen and A.Tuson (eds.) (2007)
    Research and Development in Intelligent Systems XXIII
    Springer-Verlag. ISBN 1-84628-662-X
60. V.Grover, M.A.Bramer and R.Adderley (2007)
    Review of Current Crime Prediction Techniques
    In Applications and Innovations in Intelligent Systems XIV, Springer Verlag, pp. 233-237. ISBN 1-84628-665-4.
61. X.Wang and M.A.Bramer (2007)
    Exploring Web Search Results Clustering
    In Research and Development in Intelligent Systems XXIII, Springer Verlag, pp. 393-397. ISBN 1-84628-662-X.
62. V.Grover, M.A.Bramer and R.Adderley (2006)
    Review of Current Crime Prediction Techniques expanded version)
    University of Portsmouth, School of Computing, Research Report UoP-AI-2006-002.
63. X.Wang and M.A.Bramer (2006)
    Exploring Web Search Results Clustering [expanded version]
    University of Portsmouth, School of Computing, Research Report UoP-AI-2006-001.
64. M.A.Bramer (ed.) (2006)
    Artificial Intelligence in Theory and Practice
    Springer Science+Business Media. ISBN 0-387-34654-6.
65. M.A.Bramer (ed.) (2006)
    Special Issue of Knowledge Based Systems Journal
    Vol. 19, No. 5. September 2006. Elsevier.
66. M.A.Bramer (2006)
    An Expert System Delivery Environment for the World Wide Web
    In Artificial Intelligence Applications and Innovations: the third IFIP Conference on Artificial Intelligence Applications and Innovations, Springer, pp. 129-136. ISBN 0-387-34223-0.
67. I.Maglogiannis, K.Karpouzis and M.A.Bramer (2006).
    Artificial Intelligence Applications and Innovations: the third IFIP Conference on Artificial Intelligence Applications and Innovations
    Springer. ISBN 0-387-34223-0
68. M.A.Bramer, F.Coenen and T.Allen (eds.) (2006)
    Research and Development in Intelligent Systems XXII
    Springer-Verlag. ISBN 1-84628-225-X
69. M.A.Bramer (2005)
    Inducer: A Public Domain Workbench for Data Mining
    International Journal of Systems Science, Vol. 36, No. 14, pp. 909-919. ISSN 0020-7721.
70. H.Benbrahim and M.A.Bramer (2005).
    Experiments in Hypertext Categorization
    Expert Update, Vol. 8, No. 2, Autumn 2005, pp. 40-46. ISSN 1465-4091.
71. M.Bramer and V.Terziyan (eds.) (2005)
    Industrial Applications of Semantic Web
    Springer. ISBN 0-387-28568-7
72. Max Bramer (2005)
    Logic Programming With Prolog
    Springer-Verlag. ISBN 1-85233-938-1
73. M.A.Bramer (ed.) (2005)
    Special Issue of Knowledge Based Systems Journal
    Vol. 18, Nos.4-5. Summer 2005. Elsevier.
74. M.A.Bramer, F.Coenen and T.Allen (eds.) (2005)
    Research and Development in Intelligent Systems XXI
    Springer-Verlag. ISBN 1-85233-907-1
75. M.A.Bramer (2004)
    A Public Domain Classification Workbench for Data Mining
    Systems Science, Vol. 30, No. 4, pp. 91-102. ISSN 0137-1223.
76. H.Benbrahim and M.A.Bramer (2004)
    Neighbourhood Exploitation in Hypertext Categorization
    In Proceedings of the Twenty-fourth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, Cambridge, December 2004, pp. 258-268. ISBN 1-85233-907-1
77. R.Rastogi, K.Morik, M.Bramer and X.Wu (eds.) (2004)
    Proceedings of the Fourth IEEE International Conference on Data Mining: ICDM 2004
    IEEE. ISBN 0-7695-2142-8
78. H.Benbrahim and M.A.Bramer (2004)
    An Empirical Study for Hypertext Categorization
    Proceedings of the 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE SMC 2004), The Hague, October 2004.
    Systems, Man and Cybernetics, Volume 6, pp. 5952-5957. DOI: 10.1109/ICSMC.2004.1401147
79. M.A.Bramer (2004)
    A Public Domain Classification Workbench for Data Mining
    In Z.Bubnicki and A.Grzech (eds.), Proceedings of the 15th International Conference on Systems Science (Wroclaw, Poland, September 2004), Volume III, pp. 61-72. ISBN 83-7085-806-6.
    Reprinted in Systems Science, Vol. 30, No. 4, 2004, pp. 91-102. ISSN 0137-1223.
80. M.A. Bramer and V. Devedzic (eds.) (2004)
    Artificial Intelligence Applications and Innovations
    Kluwer Academic Publishers. ISBN 1-4020-8150-2.
81. H.Benbrahim and M.A.Bramer (2004)
    Impact on Performance of Hypertext Classification of Selective Rich HTML Capture
    In Artificial Intelligence Applications and Innovations, Kluwer Academic Publishers, pp. 279-291. ISBN 1-4020-8150-2.
82. M.A.Bramer (2004)
    The Inducer Rule Induction Workbench
    In R.Yager and V.Sgurev (eds.), Proceedings of the Second IEEE International Conference on Intelligent Systems (IEEE IS'04), Varna, Bulgaria, June 2004, pp. 190-195. ISBN 0-7803-8278-1
83. M.A.Bramer (ed.) (2004)
    Special Issue of Knowledge Based Systems Journal
    Vol. 17, Nos. 2-3, Summer 2004. Elsevier.
84. M.A.Bramer, R.Ellis and A.L.Macintosh (eds.) (2004)
    Applications and Innovations in Intelligent Systems XI
    Springer-Verlag. ISBN 1-85233-779-6
85. M.A.Bramer (2003)
    Knowledge Web: A Public Domain Expert System Delivery Environment
    2003 IEEE International Conference on Systems, Man And Cybernetics, pp. 2162-2168. ISBN 0-7803-7952-7
86. R.Amin, M.A.Bramer and R.Emslie (2003)
    Intelligent Data Analysis for Conservation: Experiments with Rhino Horn Fingerprint Identification
    Knowledge Based Systems, Vol. 16, Issues 5-6, July 2003, pp. 329-336. ISSN 0950-7051
    (Also included in Applications and Innovations in Intelligent Systems X (eds. A.Macintosh, R.Ellis and F.Coenen), Springer-Verlag, pp. 207-222. ISBN 1-85233-673-0)
87. M.A.Bramer (ed.) (2003)
    Special Issue of Knowledge Based Systems Journal
    Vol. 16, Nos. 5-6, July 2003. Elsevier
88. M.A.Bramer, A.Preece and F.Coenen (eds.) (2003)
    Research and Development in Intelligent Systems XIX
    Springer-Verlag. ISBN 1-85233-674-9
89. M.A.Bramer (2002)
    Using J-Pruning to Reduce Overfitting of Classification Rules in Noisy Domains
    In Database and Expert Systems Applications (eds. A.Hameurlain, R.Cicchetti and R.Traunm�ller), Springer-Verlag, pp. 433-442. ISBN 3-540-44126-3
90. M.A.Bramer (2002)
    An Information-Theoretic Approach to the Pre-pruning of Classification Rules
    In Intelligent Information Processing (eds. M.Musen, B.Neumann and R.Studer), Kluwer, pp. 201-212. ISBN 1-4020-7171-X
91. M.A.Bramer (2002)
    Pre-pruning Classification Trees to Reduce Overfitting in Noisy Domains
    In Intelligent Data Engineering and Automated Learning - IDEAL 2002 (eds. H.Yin et al.), Springer-Verlag, 2002, pp. 7-12. ISBN 3-540-44025-9
92. M.A.Bramer (2002)
    Using J-Pruning to Reduce Overfitting in Classification Trees
    Knowledge Based Systems, Vol. 15, Issues 5-6, pp. 301-308, July 2002. ISSN 0950-7051
    (Also included in Research and Development in Intelligent Systems XVIII, Springer-Verlag, pp. 25-38, 2001. ISBN 1-85233-535-1)
93. M.A.Bramer (ed.) (2002)
    Special Issue of Knowledge Based Systems Journal
    Vol. 15, Nos. 5-6. Elsevier
94. M.A.Bramer, F.Coenen and A.Preece (eds.) (2002)
    Research and Development in Intelligent Systems XVIII
    Springer-Verlag.
95. M.A.Bramer (ed.) (2001)
    Special Issue of Knowledge Based Systems Journal
    Vol. 14, Nos.3-4. Elsevier
96. M.A.Bramer, A.Preece and F.Coenen (eds.) (2001)
    Research and Development in Intelligent Systems XVII
    Springer-Verlag.
97. M.A.Bramer (2000)
    Inducer: a Rule Induction Workbench for Data Mining
    In Proceedings of the IFIP World Computer Congress Conference on Intelligent Information Processing
    (eds. Z.Shi, B.Faltings and M.Musen) Publishing House of Electronics Industry (Beijing), pp. 499-506. ISBN 3 901882 06 5
98. M.A.Bramer (ed.) (2000)
    Special Issue of Knowledge Based Systems Journal
    Vol. 13, Nos. 2-3. Elsevier
99. M.A.Bramer (2000)
    Automatic Induction of Classification Rules from Examples Using N-Prism
    In Research and Development in Intelligent Systems XVI. Springer-Verlag, pp. 99-121
100. M.A.Bramer, A.Macintosh and F.Coenen (eds.) (2000)
     Research and Development in Intelligent Systems XVI
     Springer-Verlag
101. M.A.Bramer (1999)
     Knowledge Discovery and Data Mining
     Institution of Electrical Engineers. ISBN 0 85296 767 5
102. M.A.Bramer (ed.) (1999)
     Special Issue of Knowledge Based Systems Journal
     Vol. 12, Nos. 5-6. Elsevier
103. K.Nazar and M.A.Bramer (1999)
     Estimating Concept Difficulty with Cross-Entropy
     In Knowledge Discovery and Data Mining (ed. M.A.Bramer), IEE, 1999.
104. R.Miles, M.Moulton and M.A.Bramer (eds.) (1999)
     Research and Development in Expert Systems XV
     Springer-Verlag
105. R.Milne, A.Macintosh and M.A.Bramer (eds.) (1999)
     Applications and Innovations in Expert Systems VI
     Springer-Verlag
106. M.A.Bramer (ed.) (1998)
     Special Issue of Knowledge Based Systems Journal
     Vol. 11, Nos. 5-6. Elsevier
107. K.Nazar and M.A.Bramer (1997)
     Concept Dispersion, Feature Interaction and Their Effect on Particular Sources of Bias in Machine Learning
     In Research and Development in Expert Systems XIV (eds. J.Hunt and R.Miles) SGES Publications, pp. 7-23.
     Reprinted in Knowledge Based Systems, Vol. 11, Nos.5-6. (1998).
108. M.A.Bramer (1997)
     Rule Induction in Data Mining: Concepts and Pitfalls (1)
     Data Warehouse Report, No. 10, pp. 11-17, Summer 1997. Data Warehouse Network.
109. M.A.Bramer (1997)
     Rule Induction in Data Mining: Concepts and Pitfalls (2)
     Data Warehouse Report, No. 11, pp. 22-27, Autumn 1997. Data Warehouse Network
110. W.Liu, A.P.White, S.G.Thompson and M.A.Bramer (1997)
     Techniques for Dealing with Missing Values in Classification
     In Advances in Intelligent Data Analysis: Reasoning About Data (Proceedings of the Second International Symposium on Intelligent Data Analysis) (eds. X. Liu, P. Cohen and M. Berthold), Springer-Verlag, pp. 527-536. LNCS 1280
111. S.G.Thompson and M.A.Bramer (1996)
     Subsetting as an Approach to Distributed Learning
     In Research and Development in Expert Systems XIII (eds. J.L.Nealon and J.Hunt), SGES Publications, pp. 217-231
112. M.A.Bramer (1996)
     Induction of Classification Rules from Examples: A Critical Review
     Proceedings of Data Mining 96, London, April 1996, Unicom Conferences, pp. 140-166. Unicom.
     Also included in:
     Proceedings of Data Mining and Data Warehouse 96, London, November 1996, Unicom Conferences,
           pp. 34-60. Unicom.
     Proceedings of Data Warehouse 97, Madrid, April 1997. Instituto Superior de Tecnicas y Practicas Bancarias.
     Proceedings of Data Warehouse 97, London, June 1997. Data Warehouse Network.