Footprint-based retrieval

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

Volumn 1650, Issue , 1999, Pages 343-357

  Smyth, Barry ^a   McKenna, Elizabeth ^a  

^a UNIVERSITY COLLEGE DUBLIN   (Ireland)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; EFFICIENCY;

CASE BASED REASONING SYSTEMS; ITS EFFICIENCIES; QUALITY CHARACTERISTIC; QUALITY FEATURES; RETRIEVAL ALGORITHMS; RETRIEVAL TECHNIQUES;

CASE BASED REASONING;

EID: 84948153142     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-48508-2_25     Document Type: Conference Paper

References (15)

1. Aha, D.W., Kibler, D., and Albert, M.K.: Instance-Based Learning Algorithms. Machine Learning 6 (1991) 37-66.
2. Brown, M.G.: An Underlying Memory Model to Support Case Retrieval. In: Topics in Case-Based Reasoning. Lecture Notes in Artificial Intelligence, Vol. 837. Springer-Verlag, Berlin Heidelberg New York (1994) 132-143.
3. Dasarathy, B.V.: Nearest Neighbor Norms: NN Pattern Classification Techniques. IEEE Press, Los Alamitos, California (1991)
4. Hart, P.E.: The Condensed Nearest Neighbor Rule. IEEE Transactions on Information Theory, 14 (1967) 515-516.
5. Leake, D.B., Kinley, A., and Wilson, D.: Case-Based Similarity Asessment: Estimating Adaptability from Experience. In: Proceedings of the 14th National Conference on Artificial Intelligence. AAAI Press (1997)
6. Lenz, M.: Applying Case Retrieval Nets to Diagnostic Tasks in Technical Domains. In: Smith, I. & Faltings, B. (eds.): Advances in Case-Based Reasoning. Lecture Notes in Artificial Intelligence, Vol. 1168. Springer-Verlag, Berlin Heidelberg New York (1996) 219-233
7. Lieber, J.: A Criterion of Comparison between two Case-Bases. In: Haton, J-P., Keane, M., and Manago, M. (eds.): Advances in Case-Based Reasoning. Lecture Notes in Artificial Intelligence, Vol. 984. Springer-Verlag, Berlin Heidelberg New York (1994) 87-100
8. Minton, S.: Qualitative Results Concerning the Utility of Explanation-Based Learning, Artificial Intelligence, 42(2, 3) (1990) 363-391
9. Schaaf, J. W.: Fish and Shrink: A Next Step Towards Efficient Case Retrieval in Large-Scale Case-Bases. In: Smith, I. & Faltings, B. (eds.): Advances in Case-Based Reasoning. Lecture Notes in Artificial Intelligence, Vol. 1168. Springer-Verlag, Berlin Heidelberg New York (1996) 362-376
10. Smyth, B. and Keane M. T.: Adaptation-Guided Retrieval: Questioning the Similarity Assumption in Reasoning. Artificial Intelligence 102 (1998) 249-293
11. Smyth, B. & Keane, M.T.: Remembering to Forget: A Competence Preserving Deletion Policy for Case-Based Reasoning Systems. In: Proceedings of the 14th International Joint Conference on Artificial Intelligence. Morgan-Kaufmann. (1995) 377-382
12. Smyth, B. & McKenna, E.: Modelling the Competence of Case-Bases. In: Smyth, B. & Cunningham, P. (eds.): Advances in Case-Based Reasoning. Lecture Notes in Artificial Intelligence, Vol. 1488. Springer-Verlag, Berlin Heidelberg New York (1998). 208-220
13. Veloso, M. Flexible Strategy Learning: Analogical Replay of Problem Solving Episodes. Proceedings of the 12th National Conference on Artificial Intelligence (1994) 595-600.
14. Wess, S., Althoff, K-D., Derwand, G.: Using k-d Trees to Improve the Retrieval Step in Case-Based Reasoning. In: Topics in Case-Based Reasoning. Lecture Notes in Artificial Intelligence, Vol. 837. Springer-Verlag, Berlin Heidelberg New York (1994) 167-181
15. Wolverton, M., and Hayes-Roth, B.: Retrieving Semantically Distant Analogies with Knowledge-Directed Spreading Activation. In: Proceedings of the 12th National Conference on Artificial Intelligence, (1994) 56-61.