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Case-based reasoning using dominance-based decision rules

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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Case-based reasoning using dominance-based decision rules. / Szelag, M.; Greco, Salvatore; Blaszczynski, J.; Slowinski, R.

Rough sets and knowledge technology: proceedings of the 6th international conference. ed. / J. Yao; S. Ramanna; G. Wang; Z. Suraj. Vol. 6954 9654. ed. Berlin : Springer, 2011. p. 404-413 (Lecture notes in computer science; No. 9654).

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Harvard

Szelag, M, Greco, S, Blaszczynski, J & Slowinski, R 2011, Case-based reasoning using dominance-based decision rules. in J Yao, S Ramanna, G Wang & Z Suraj (eds), Rough sets and knowledge technology: proceedings of the 6th international conference. 9654 edn, vol. 6954, Lecture notes in computer science, no. 9654, Springer, Berlin, pp. 404-413. https://doi.org/10.1007/978-3-642-24425-4_53

APA

Szelag, M., Greco, S., Blaszczynski, J., & Slowinski, R. (2011). Case-based reasoning using dominance-based decision rules. In J. Yao, S. Ramanna, G. Wang, & Z. Suraj (Eds.), Rough sets and knowledge technology: proceedings of the 6th international conference (9654 ed., Vol. 6954, pp. 404-413). (Lecture notes in computer science; No. 9654). Springer. https://doi.org/10.1007/978-3-642-24425-4_53

Vancouver

Szelag M, Greco S, Blaszczynski J, Slowinski R. Case-based reasoning using dominance-based decision rules. In Yao J, Ramanna S, Wang G, Suraj Z, editors, Rough sets and knowledge technology: proceedings of the 6th international conference. 9654 ed. Vol. 6954. Berlin: Springer. 2011. p. 404-413. (Lecture notes in computer science; 9654). https://doi.org/10.1007/978-3-642-24425-4_53

Author

Szelag, M. ; Greco, Salvatore ; Blaszczynski, J. ; Slowinski, R. / Case-based reasoning using dominance-based decision rules. Rough sets and knowledge technology: proceedings of the 6th international conference. editor / J. Yao ; S. Ramanna ; G. Wang ; Z. Suraj. Vol. 6954 9654. ed. Berlin : Springer, 2011. pp. 404-413 (Lecture notes in computer science; 9654).

Bibtex

@inbook{a1256f4557af48fea46ea1497ba13184,
title = "Case-based reasoning using dominance-based decision rules",
abstract = "Case-based Reasoning (CBR) is a process of inferring conclusions related to a new situation by the analysis of similar cases known from the past experience. We propose to adopt in this process the Dominance-based Rough Set Approach (DRSA), that is able to handle monotonicity relationships of the type {"}the more similar is object y to object x with respect to the considered features, the closer is y to x in terms of the membership to a given fuzzy set X{"}. At the level of marginal similarity concerning single features, we consider this similarity in ordinal terms only. The marginal similarities are aggregated within decision rules underlying the general monotonicity property of comprehensive closeness of objects with respect to their marginal similarities.",
author = "M. Szelag and Salvatore Greco and J. Blaszczynski and R. Slowinski",
year = "2011",
month = oct,
doi = "10.1007/978-3-642-24425-4_53",
language = "English",
isbn = "9783642244247",
volume = "6954",
series = "Lecture notes in computer science",
publisher = "Springer",
number = "9654",
pages = "404--413",
editor = "J. Yao and S. Ramanna and G. Wang and Z. Suraj",
booktitle = "Rough sets and knowledge technology: proceedings of the 6th international conference",
edition = "9654",

}

RIS

TY - CHAP

T1 - Case-based reasoning using dominance-based decision rules

AU - Szelag, M.

AU - Greco, Salvatore

AU - Blaszczynski, J.

AU - Slowinski, R.

PY - 2011/10

Y1 - 2011/10

N2 - Case-based Reasoning (CBR) is a process of inferring conclusions related to a new situation by the analysis of similar cases known from the past experience. We propose to adopt in this process the Dominance-based Rough Set Approach (DRSA), that is able to handle monotonicity relationships of the type "the more similar is object y to object x with respect to the considered features, the closer is y to x in terms of the membership to a given fuzzy set X". At the level of marginal similarity concerning single features, we consider this similarity in ordinal terms only. The marginal similarities are aggregated within decision rules underlying the general monotonicity property of comprehensive closeness of objects with respect to their marginal similarities.

AB - Case-based Reasoning (CBR) is a process of inferring conclusions related to a new situation by the analysis of similar cases known from the past experience. We propose to adopt in this process the Dominance-based Rough Set Approach (DRSA), that is able to handle monotonicity relationships of the type "the more similar is object y to object x with respect to the considered features, the closer is y to x in terms of the membership to a given fuzzy set X". At the level of marginal similarity concerning single features, we consider this similarity in ordinal terms only. The marginal similarities are aggregated within decision rules underlying the general monotonicity property of comprehensive closeness of objects with respect to their marginal similarities.

U2 - 10.1007/978-3-642-24425-4_53

DO - 10.1007/978-3-642-24425-4_53

M3 - Chapter (peer-reviewed)

SN - 9783642244247

VL - 6954

T3 - Lecture notes in computer science

SP - 404

EP - 413

BT - Rough sets and knowledge technology: proceedings of the 6th international conference

A2 - Yao, J.

A2 - Ramanna, S.

A2 - Wang, G.

A2 - Suraj, Z.

PB - Springer

CY - Berlin

ER -

ID: 229973