{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T13:39:38Z","timestamp":1760708378351,"version":"3.37.3"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2012,2,4]],"date-time":"2012-02-04T00:00:00Z","timestamp":1328313600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2013,2]]},"DOI":"10.1007\/s10115-011-0466-5","type":"journal-article","created":{"date-parts":[[2012,2,3]],"date-time":"2012-02-03T05:47:46Z","timestamp":1328248066000},"page":"267-298","source":"Crossref","is-referenced-by-count":11,"title":["Building actions from classification rules"],"prefix":"10.1007","volume":"34","author":[{"given":"Ronan","family":"Tr\u00e9pos","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ansaf","family":"Salleb-Aouissi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marie-Odile","family":"Cordier","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"V\u00e9ronique","family":"Masson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chantal","family":"Gascuel-Odoux","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2012,2,4]]},"reference":[{"key":"466_CR1","unstructured":"Adomavicius G, Tuzhilin A (1997) Discovery of actionable patterns in databases: the action hierarchy approach. In: KDD, pp 111\u2013114"},{"key":"466_CR2","unstructured":"Ali KM, Pazzani MJ (1993) HYDRA: a noise-tolerant relational concept learning algorithm. In: Proceedings of the 13th international joint conference on artificial intelligence (IJCAI\u201993), Morgan Kaufmann, pp 1064\u20131071"},{"key":"466_CR3","unstructured":"Allen JF (1981) An interval-based representation of temporal knowledge. In: Proceedings of the 7th international conference on artificial intelligence (IJCAI\u201981), pp 221\u2013226"},{"issue":"2","key":"466_CR4","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.cageo.2008.09.003","volume":"35","author":"P Aurousseau","year":"2009","unstructured":"Aurousseau P, Gascuel-Odoux C, Squividant H, Tr\u00e9posR Tortrat F, Cordier M-O (2009) A plot drainage network as a conceptual tool for the spatialisation of surface flow pathways for agricultural catchments. Comput Geosci 35(2): 276\u2013288","journal-title":"Comput Geosci"},{"key":"466_CR5","doi-asserted-by":"crossref","unstructured":"Clark P, Boswell R (1991) Rule induction with CN2: some recent improvements. In: Proceedings of the 5th European working session on learning (EWSL\u201991), Springer, pp 151\u2013163","DOI":"10.1007\/BFb0017011"},{"key":"466_CR6","first-page":"261","volume":"3","author":"P Clark","year":"1989","unstructured":"Clark P, Niblett T (1989) The cn2 induction algorithm. Mach Learn 3: 261\u2013283","journal-title":"Mach Learn"},{"key":"466_CR7","first-page":"35","volume":"61","author":"M-O Cordier","year":"2005","unstructured":"Cordier M-O (2005) SACADEAU: a decision-aid system to improve stream-water quality. ERCIM News. Spec Issue Environ Model 61: 35\u201336","journal-title":"ERCIM News. Spec Issue Environ Model"},{"key":"466_CR8","unstructured":"Cordier M-O, Garcia F, Gascuel-Odoux C, Masson V, Salleb A, Tr\u00e9pos R (2006) SACADEAU project: recommending actions from simulation results. In: BESAI\u201906 (ECAI\u201906 workshop on binding environmental sciences and artificial intelligence), Riva del Garda, Italy, August 2006. Poster communication"},{"key":"466_CR9","unstructured":"Cordier M-O, Garcia F, Gascuel-Odoux C, Masson V Salmon-Monviola J Tortrat F, Tr\u00e9pos R (2005) A machine learning approach for evaluating the impact of land use and management practices on streamwater pollution by pesticides. In: Proceedings of international congress on modelling and simulation (MODSIM\u201905), pp 2651\u20132657. Modelling and Simulation Society of Australia and New Zealand, 12\u201315 December"},{"issue":"1","key":"466_CR10","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1109\/TSMCA.2003.812596","volume":"33","author":"Y Elovici","year":"2003","unstructured":"Elovici Y, Braha D (2003) A decision-theoretic approach to data mining. IEEE Trans Syst Man Cybern Part A 33(1): 42\u201351","journal-title":"IEEE Trans Syst Man Cybern Part A"},{"key":"466_CR11","unstructured":"Frank E, Witten IH (1998) Generating accurate rule sets without global optimization. In: Proceedings of 15th international conference on machine learning (ICML\u201998), Morgan Kaufmann, pp 144\u2013151"},{"issue":"1","key":"466_CR12","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1023\/A:1006524209794","volume":"13","author":"J F\u00fcrnkranz","year":"1999","unstructured":"F\u00fcrnkranz J (1999) Separate-and-conquer rule learning. Artif Intell Rev 13(1): 3\u201354","journal-title":"Artif Intell Rev"},{"issue":"12","key":"466_CR13","doi-asserted-by":"crossref","first-page":"1433","DOI":"10.1016\/j.envsoft.2009.06.002","volume":"24","author":"C Gascuel-Odoux","year":"2009","unstructured":"Gascuel-Odoux C, Aurousseau P, Cordier M-O, Durand P, Garcia F, Masson V, Salmon-Monviola J, Tortrat F, Tr\u00e9pos R (2009) A decision-oriented model to evaluate the effect of land use and agricultural management on herbicide contamination in stream water. Environ Model Softw 24(12): 1433\u20131446","journal-title":"Environ Model Softw"},{"key":"466_CR14","doi-asserted-by":"crossref","unstructured":"Grzymala-Busse JW (1992) LERS\u2014a system for learning from examples based on rough sets. In: Slowinski R (ed) Intelligent decision support. Handbook of applications and advances of the rough set theory. Kluwer Academic Publishers, Dordrecht, pp 3\u201318","DOI":"10.1007\/978-94-015-7975-9_1"},{"key":"466_CR15","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1145\/1656274.1656278","volume":"11","author":"M Hall","year":"2009","unstructured":"Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH (2009) The weka data mining software: an update. SIGKDD Explor 11: 10\u201318","journal-title":"SIGKDD Explor"},{"key":"466_CR16","unstructured":"He Z, Xu X, Deng S (2005) Data mining for actionable knowledge: a survey. ArXiv Computer Science e-prints"},{"issue":"3","key":"466_CR17","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1016\/j.eswa.2005.04.031","volume":"29","author":"Z He","year":"2005","unstructured":"He Z, Xu X, Deng S, Ma R (2005) Mining action rules from scratch. Expert Syst Appl 29(3): 691\u2013699","journal-title":"Expert Syst Appl"},{"key":"466_CR18","doi-asserted-by":"crossref","unstructured":"Herrera F, Carmona C, Gonz\u00e1lez P, del Jesus M (2011) An overview on subgroup discovery: foundations and applications. Knowl Inf Syst 29(3):495\u2013525. http:\/\/dx.doi.org\/10.1007\/s10115-010-0356-2","DOI":"10.1007\/s10115-010-0356-2"},{"issue":"4","key":"466_CR19","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1109\/21.286391","volume":"24","author":"M Ichino","year":"1994","unstructured":"Ichino M, Yaganduchi H (1994) Generalized minkowski metrics for mixed feature-type data analysis. IEEE Trans Syst Man Cybern 24(4): 698\u2013708","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"466_CR20","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/s10115-009-0221-3","volume":"25","author":"S Im","year":"2010","unstructured":"Im S, Ras Z, Wasyluk H (2010) Action rule discovery from incomplete data. Knowl Inf Syst 25: 21\u201333","journal-title":"Knowl Inf Syst"},{"key":"466_CR21","unstructured":"Jiang Y, Wang K, Tuzhilin A, Fu AW-C (2005) Mining patterns that respond to actions. In: ICDM, pp 669\u2013672"},{"issue":"1\u20132","key":"466_CR22","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1023\/B:MACH.0000035474.48771.cd","volume":"57","author":"N Lavra\u010d","year":"2004","unstructured":"Lavra\u010d N, Cestnik B, Gamberger D, Flach P (2004) Decision support through subgroup discovery: three case studies and the lessons learned. Mach Learn 57(1\u20132): 115\u2013143","journal-title":"Mach Learn"},{"key":"466_CR23","doi-asserted-by":"crossref","unstructured":"Ling CX, Chen T, Yang Q, Cheng J (2002) Mining optimal actions for profitable CRM. In: International conference on data mining (ICDM\u201902), pp 767\u2013770","DOI":"10.1109\/ICDM.2002.1184049"},{"key":"466_CR24","doi-asserted-by":"crossref","unstructured":"Liu B, Hsu W, Ma Y (2001) Identifying non-actionable association rules. In: Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining (KDD\u201901), ACM Press, pp 329\u2013334","DOI":"10.1145\/502512.502560"},{"key":"466_CR25","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1007\/s10115-009-0192-4","volume":"22","author":"S Liu","year":"2010","unstructured":"Liu S, Duffy AHB, Whitfield RI (2010) Boyle IM integration of decision support systems to improve decision support performance. Knowl Inf Syst 22: 261\u2013286","journal-title":"Knowl Inf Syst"},{"issue":"1","key":"466_CR26","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1093\/comjnl\/bxh151","volume":"49","author":"J Ma","year":"2006","unstructured":"Ma J, Hayes P (2006) Primitive intervals versus point-based intervals: rivals or allies?. Comput J 49(1): 32\u201341","journal-title":"Comput J"},{"key":"466_CR27","unstructured":"Malerba D, Esposito F, Gioviale V, Tamma V (2001) Comparing dissimilarity measures in symbolic data analysis. In: Joint conferences on new techniques and technologies for statistcs and exchange of technology and know-how (ETK-NTTS\u201901), pp 473\u2013481"},{"key":"466_CR28","unstructured":"Michalski R-S (1973) Aqval\/1\u2014computer implementation of a variable-valued logic system vl_1 and examples of its application to pattern recognition. In: Proceedings of the 1st international joint conference on pattern recognition (IJCPR\u201973), pp 3\u201317"},{"key":"466_CR29","unstructured":"Michalski RS, Mozetic I, Hong J (1986) The multi-purpose incremental learning system aq15 and it testing application to three medical domains. In: Proceedings of AAAI-86, pp 1041\u20131045"},{"issue":"2","key":"466_CR30","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/0004-3702(82)90040-6","volume":"18","author":"TM Mitchell","year":"1982","unstructured":"Mitchell TM (1982) Generalization as search. Artif Intell 18(2): 203\u2013226","journal-title":"Artif Intell"},{"key":"466_CR31","unstructured":"Newman DJ, Asuncion A (2007) UCI machine learning repository"},{"key":"466_CR32","volume-title":"Rough sets: theoretical aspects of reasoning about data","author":"Z Pawlak","year":"1992","unstructured":"Pawlak Z (1992) Rough sets: theoretical aspects of reasoning about data. Kluwer Academic Publishers, Norwell"},{"key":"466_CR33","unstructured":"Piatetsky-Shapiro G, Matheus C (1994) The interestingness of deviations. In: AAAI workshop on knowledge discovery in databases. AAAI Press, pp 25\u201336"},{"key":"466_CR34","unstructured":"Quinlan JR (1987) Generating production rules from decision trees. In: Proceedings of the 10th international conference on artificial intelligence (IJCAI\u201987), Kaufmann, pp 304\u2013307"},{"key":"466_CR35","unstructured":"Ras ZW, Dardzinska A (2006) Action rules discovery, a new simplified strategy. In: Esposito F, Ras ZW, Malerba D, Semeraro G (eds) Proceedings of the international symposiumon methodologies for intelligent systems, (ISMIS\u201906), vol 4203. Springer, pp 445\u2013453"},{"key":"466_CR36","doi-asserted-by":"crossref","unstructured":"Ras ZW, Tsay L-S (2003) Discovering extended action-rules, system dear. In: Intelligent information systems (IIS\u201903), Spinger, pp 293\u2013300","DOI":"10.1007\/978-3-540-36562-4_31"},{"key":"466_CR37","unstructured":"Ras ZW, Tzacheva AA (2003) Discovering semantic inconsistencies to improve action rules mining. In: Intelligent information systems (IIS\u201903), Spinger, pp 301\u2013310"},{"key":"466_CR38","doi-asserted-by":"crossref","unstructured":"Ras ZW, Tzacheva AA, Tsay L-S, Gurdal O (2005) Mining for interesting action rules. In: Proceedings of the 2005 IEEE\/WIC\/ACM international conference on intelligent agent technology (IAT\u201905), IEEE, pp 187\u2013193","DOI":"10.1109\/IAT.2005.98"},{"key":"466_CR39","unstructured":"Ras ZW, Wieczorkowska A (2000) Action-rules: how to increase profit of a company. In: European conference on principles and practice of knowledge discovery in databases (PKDD\u201900), pp 587\u2013592"},{"key":"466_CR40","unstructured":"Salleb-Aouissi A, Tr\u00e9pos R, Cordier M-O, Masson V (2008) From classification rules to action recommendation. Technical report ccls-08-01, Center for computational learning systems, New York, Mars"},{"key":"466_CR41","doi-asserted-by":"crossref","unstructured":"Salmon-Monviola J, Gascuel-Odoux C, Garcia F, Tortrat F, Cordier M-O, Masson V, Tr\u00e9pos R (2011) Simulating the effect of technical and environmental constraints on the spatio-temporal distribution of herbicide applications and stream losses. Agric Ecosyst Environ 140:382\u2013394","DOI":"10.1016\/j.agee.2010.12.022"},{"key":"466_CR42","unstructured":"Sebag M (1996) Delaying the choice of bias: a disjunctive version space approach. In: International conference on machine learning (ICML\u201996), pp 444\u2013452"},{"key":"466_CR43","doi-asserted-by":"crossref","first-page":"970","DOI":"10.1109\/69.553165","volume":"8","author":"A Silberschatz","year":"1996","unstructured":"Silberschatz A, Tuzhilin A (1996) What makes patterns interesting in knowledge discovery systems. IEEE Trans Knowl Data Eng 8: 970\u2013974","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"466_CR44","doi-asserted-by":"crossref","unstructured":"Tr\u00e9pos R, Masson V, Cordier M-O, Gascuel-Odoux C, Salmon-Monviola J (2012) Mining simulation data by rule induction to determine critical source areas of stream water pollution by herbicides. Comput Electron Agric 2656. doi: 10.1016\/j.compag.2012.01.006","DOI":"10.1016\/j.compag.2012.01.006"},{"key":"466_CR45","unstructured":"Tr\u00e9pos R, Cordier M-O, Gascuel-Odoux C, Masson V (2008) Symbolic learning of relationships between agricultural activities and water quality from simulations for decision support. In: Geophysical research abstracts, volume 10, Vienna, Austria, 13\u201318 April 2008. European Geosciences Union General Assembly 2008. Poster communication"},{"key":"466_CR46","doi-asserted-by":"crossref","unstructured":"Tr\u00e9pos R, Salleb A, Cordier M-O, Masson V, Gascuel-Odoux C (2005) A distance based approach for action recommendation. In: Proceedings of European conference on machine learning (ECML\u201905), Springer, pp 425\u2013434","DOI":"10.1007\/11564096_41"},{"issue":"1\u20132","key":"466_CR47","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1080\/09528130512331315855","volume":"17","author":"L-S Tsay","year":"2005","unstructured":"Tsay L-S, Ras ZW (2005) Action rules discovery: system DEAR2, method and experiments. J Exp Theor Artif Intell 17(1\u20132): 119\u2013128","journal-title":"J Exp Theor Artif Intell"},{"key":"466_CR48","unstructured":"Tzacheva AA, Ras ZW (2005) Action rules mining. In: Ras ZW (ed) Special issue on knowledge discovery. International journal of intelligent systems, vol 20, no 7. pp 719\u2013736"},{"key":"466_CR49","unstructured":"Yang Q, Cheng H (2002) Mining case bases for action recommendation. In: ICDM, pp 522\u2013529"},{"key":"466_CR50","doi-asserted-by":"crossref","unstructured":"Yang Q, Yin J, Ling CX, Chen T (2003) Postprocessing decision trees to extract actionable knowledge. In: International conference on data mining (ICDM\u201903), pp 685\u2013688","DOI":"10.1109\/ICDM.2003.1251008"},{"key":"466_CR51","doi-asserted-by":"crossref","unstructured":"Zhao K, Liu B, Tirpak TM, Xiao W (2005) Opportunity map: a visualization framework for fast identification of actionable knowledge. In: Proceedings of the 14th ACM international conference on information and knowledge management (CIKM\u201905), ACM, pp 60\u201367","DOI":"10.1145\/1099554.1099568"},{"key":"466_CR52","doi-asserted-by":"crossref","unstructured":"Zliobaite I, Pechenizkiy M (2010) Learning with actionable attributes: attention\u2014boundary cases! Data mining workshops, international conference on data mining, 0:1021\u20131028","DOI":"10.1109\/ICDMW.2010.140"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-011-0466-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10115-011-0466-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-011-0466-5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,23]],"date-time":"2019-06-23T01:40:42Z","timestamp":1561254042000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10115-011-0466-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,2,4]]},"references-count":52,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2013,2]]}},"alternative-id":["466"],"URL":"https:\/\/doi.org\/10.1007\/s10115-011-0466-5","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"type":"print","value":"0219-1377"},{"type":"electronic","value":"0219-3116"}],"subject":[],"published":{"date-parts":[[2012,2,4]]}}}