A context-aware approach to selecting adaptations for case-based reasoning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8175 LNAI, Issue , 2013, Pages 101-114

  Jalali, Vahid ^a   Leake, David ^a  

^a INDIANA UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTATION RULES; CONTEXT INDEPENDENT; CONTEXT-AWARE APPROACHES; CONTEXT-AWARENESS; CONTEXTUAL INFORMATION; PERFORMANCE BENEFITS; SOLUTION ACCURACY; STANDARD MACHINES;

ARTIFICIAL INTELLIGENCE;

COMPUTER SCIENCE;

EID: 84889562539     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40972-1_8     Document Type: Conference Paper

References (17)

1. Mantaras, R., McSherry, D., Bridge, D., Leake, D., Smyth, B., Craw, S., Faltings, B., Maher, M., Cox, M., Forbus, K., Keane, M., Aamodt, A., Watson, I.: Retrieval, reuse, revision, and retention in CBR. Knowledge Engineering Review 20(3) (2005)
2. Leake, D.: Learning adaptation strategies by introspective reasoning about memory search. In: Proceedings of the AAAI 1993 Workshop on Case-Based Reasoning, pp. 57-63. AAAI Press, Menlo Park (1993)
3. Hanney, K., Keane, M.: The adaptation knowledge bottleneck: How to ease it by learning from cases. In: Leake, D.B., Plaza, E. (eds.) ICCBR 1997. LNCS, vol. 1266, pp. 359-370. Springer, Heidelberg (1997)
4. Wilke, W., Vollrath, I., Althoff, K.D., Bergmann, R.: A framework for learning adaptation knowledge based on knowledge light approaches. In: Proceedings of the Fifth German Workshop on Case-Based Reasoning, pp. 235-242 (1997)
5. Bonissone, P., Cheetham, W.: Financial applications of fuzzy case-based reasoning to residential property valuation. In: Proceedings of the Sixth IEEE International Conference on Fuzzy Systems, vol. 1, pp. 37-44 (1997)
6. Hanney, K.: Learning adaptation rules from cases. Master's thesis, Trinity College, Dublin (1997)
7. McSherry, D.: An adaptation heuristic for case-based estimation. In: Smyth, B., Cunningham, P. (eds.) EWCBR 1998. LNCS (LNAI), vol. 1488, pp. 184-195. Springer, Heidelberg (1998)
8. Patterson, D., Rooney, N., Galushka, M.: A regression based adaptation strategy for case-based reasoning. In: Proceedings of the Eighteenth Annual National Conference on Artificial Intelligence, pp. 87-92. AAAI Press (2002)
9. Policastro, C.A., Carvalho, A.C., Delbem, A.C.: A hybrid case adaptation approach for case-based reasoning. Applied Intelligence 28(2), 101-119 (2008)
10. Dey, A.: Understanding and using context. Personal Ubiquitous Computing 5(1), 4-7 (2001)
11. Brézillon, P.: Context in problem solving: A survey. The Knowledge Engineering Review 14(1), 1-34 (1999)
12. McDonnell, N., Cunningham, P.: A knowledge-light approach to regression using case-based reasoning. In: Roth-Berghofer, T.R., Göker, M.H., Güvenir, H.A. (eds.) ECCBR 2006. LNCS (LNAI), vol. 4106, pp. 91-105. Springer, Heidelberg (2006)
13. Jalali, V., Leake, D.: Extending case adaptation with automatically-generated ensembles of adaptation rules. In: Delany, S.J., Ontañón, S. (eds.) ICCBR 2013. LNCS, vol. 7969, pp. 188-202. Springer, Heidelberg (2013)
14. Frank, A., Asuncion, A.: UCI machine learning repository (2010), http://archive.ics.uci.edu/ml
15. Torgo, L.: Lus torgo - regression data sets, http://www.dcc.fc.up.pt/- ltorgo/Regression/DataSets.html
16. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. SIGKDD Explor. Newsl. 11(1), 10-18 (2009)
17. Jalali, V., Leake, D.: On deriving adaptation rule confidence from the rule generation process. In: Delany, S.J., Ontañón, S. (eds.) ICCBR 2013. LNCS, vol. 7969, pp. 179-187. Springer, Heidelberg (2013)