Non-classical Logic in an Intelligent Assessment Sub-system

1. Agrawal, R., Imielinski, T., Swami, A.: Mining association rules between sets of items in large databases. In: Proceedings of ACM SIGMOD international conference on management of data, Washington, DC, USA, pp. 207–216. ACM Press, New York (1993)

   Google Scholar 

2. Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Verkamo, A.I.: Fast discovery of association rules. In: Uthurusamy, F., Piatetsky-Shapiro, G., Smyth, P. (eds.) Advances in Knowledge discovery of association rules, pp. 307–328. MIT Press, Cambridge (1996)

   Google Scholar 

3. Agrawal, R., Srikant, R.: Fast algorithm for mining association rules. In: Proceedings of the 20th very large data base conference, Santiago, Chile, pp. 487–489 (1994)

   Google Scholar 

4. Arnott, D., Pervan, G.G.: A critical analysis of decision support systems research. Journal of Information Technology 20(2), 67–87 (2005)

   Article  Google Scholar 

5. Baskerville, R., Myers, M.: Information Systems as a Reference Discipline. MIS Quarterly 26(1), 1–14 (2002)

   Google Scholar 

6. Bastide, T., Taouil, R., Pasquier, N., Stumme, G., Lakhal, L.: Mining frequent patterns with counting inference. SIGKDD explorations, Special issue on scalable algorithms 2(2), 71–80 (2000)

   Google Scholar 

7. Belnap, N.J.: A useful four valued logic. In: Dunn, J.M., Epstain, G. (eds.) Modern uses of multiple-valued logic, pp. 8–37. D. Reidel Publishing Co., Dordrecht (1977)

   Google Scholar 

8. Brin, S., Motwani, R., Ullmann, J.D., Tsur, S.: Dynamic itemset counting and implication rules for market basket data. In: Proceedings of the ACM SIGKDD international conference on management of data, Tuscon, AZ, USA, pp. 255–264 (1997)

   Google Scholar 

9. Carpineto, C., Romano, G.: Concept Data Analysis: Theory and Applications. John Wiley and Sons, Ltd., Chichester (2004)

   MATH  Google Scholar 

10. Davey, B.A., Priestley, H.A.: Introduction to lattices and order. Cambridge University Press, Cambridge (2005)

    Google Scholar 

11. Delgado, M., Sanchez, D., Martin-Bautista, M.J., Vila, M.A.: Mining association rules with improved semantics in medical databases. Artificial Intelligence in Medicine 21(1-3) (2001)

    Google Scholar 

12. Felix, P., Fraga, S., Marin, R., Barro, S.: Linguistic representation of fuzzy temporal profiles. International Journal of Uncertainty, Fuzziness and Know ledge Based Systems 7(3), 243–257 (1999)

    Article  MATH  Google Scholar 

13. Fitting, M.: Kleene’s Logic, Generalized. Journal of Logic and Computation 1(6), 797–810 (1991)

    Article  MATH  Google Scholar 

14. Ganter, B., Stumme, G., Wille, R.: Formal Concept Analysis. LNCS (LNAI), vol. 3626. Springer, Heidelberg (2005)

    Google Scholar 

15. Garcia, O.N., Moussavi, M.: A Six-Valued Logic for Representing Incomplete Knowledge. In: ISMVL. Proc. of the 20th International Symposium on Multiple-Valued Logic, Charlotte, NC, USA, May 1990, pp. 110–114. IEEE Computer Society Press, Los Alamitos (1990)

    Google Scholar 

16. Gurfinkel, A., Chechik, M.: Yasm: Model-Checking Software with Belnap Logic. Technical Report 470, University of Toronto (April 2005)

    Google Scholar 

17. Malerba, D., Lisi, F.A., Appice, A., Sblendorio, F.: Mining spatial association rules in census data: a relational approach. In: Proceedings of the ECML/PKDD’02 workshop on mining official data, University Printing House, Helsinki, pp. 80–93 (2002)

    Google Scholar 

18. Merceron, A., Yacef, K.: A Web-based Tutoring Tool with Mining Facilities to Improve Learning and Teaching. In: Verdejo, F., Hoppe, U. (eds.) Proceedings of 11th International Conference on Artificial Intelligence in Education, Sydney, IOS Press, Amsterdam (2003)

    Google Scholar 

19. Moussavi, M., Garcia, N.: A Six-Valued Logic and its application to artificial intelligence. In: Proc. of the Fift Southeastern Logic Symposium, UNC-Charlotte, NC, USA, IEEE Computer Society Press, Los Alamitos (1989)

    Google Scholar 

20. Mulsliner, D.J., Durfee, E.H., Shin, K.G.: CIRCA: A cooperative intelligent real-time control architecture. Trans. on Systems, Man and Cybernetics 23(6), 1561–1574 (1993)

    Article  Google Scholar 

21. Pasquier, N., Bastide, T., Taouil, R., Lakhal, L.: Efficient mining of association rules using closed itemset lattices. Journal of Information Systems 24(1), 25–46 (1999)

    Article  Google Scholar 

22. Pecheanu, E., Segal, C., Stefanescu, D.: Content modeling in Intelligent Instructional Environment. LNCS (LNAI), vol. 3190, pp. 1229–1234. Springer, Heidelberg (2003)

    Google Scholar 

23. Sakama, C.: Ordering default theories. In: Proceedings of the 18th International Joint Conference on Artificial Intelligence, pp. 839–844. Morgan Kaufmann, Los Altos, CA (2003)

    Google Scholar 

24. Sakama, C.: Ordering default theories and nonmonotonic logic programs. Theoretical Computer Science 338(1-3), 127–152 (2005)

    Article  MATH  Google Scholar 

25. Tafertshofer, P., Granz, A., Antreich, K.J.: Igraine-an implication GRaph-bAsed engINE for fast implication, justification and propagation. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 19(8), 907–927 (2000)

    Article  Google Scholar 

26. Wagner, G. (ed.): Vivid Logic. LNCS, vol. 764. Springer, Heidelberg (1994)

    MATH  Google Scholar 

27. Wille, R.: Concept lattices and conceptual knowledge systems. Computers Math. Applic. 23(6-9), 493–515 (1992)

    Article  MATH  Google Scholar 

28. Zaki, M.J.: Generating non-redundant association rules. In: Proceedings of the 6th ACM SIGKDD international conference on knowledge discovery and data mining, Boston, USA, pp. 34–43. ACM Press, New York (2000)

    Chapter  Google Scholar 

29. Zaki, M.J., Hsiao, C.-J.: CHARM: An efficient algorithm for closed itemset mining. In: Proceedings of the 2nd SIAM international conference on data mining, Arlington, VA, USA, pp. 34–43 (2002)

    Google Scholar 

Download references