{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T13:52:09Z","timestamp":1760709129288,"version":"3.41.0"},"reference-count":87,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2016,8,18]],"date-time":"2016-08-18T00:00:00Z","timestamp":1471478400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Inf Syst Front"],"published-print":{"date-parts":[[2018,4]]},"DOI":"10.1007\/s10796-016-9690-6","type":"journal-article","created":{"date-parts":[[2016,8,18]],"date-time":"2016-08-18T05:47:01Z","timestamp":1471499221000},"page":"401-416","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["A multi-objective model for discovering high-quality knowledge based on data quality and prior knowledge"],"prefix":"10.1007","volume":"20","author":[{"given":"Qi","family":"Liu","sequence":"first","affiliation":[]},{"given":"Gengzhong","family":"Feng","sequence":"additional","affiliation":[]},{"given":"Nengmin","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5505-0986","authenticated-orcid":false,"given":"Giri Kumar","family":"Tayi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,8,18]]},"reference":[{"key":"9690_CR1","doi-asserted-by":"crossref","unstructured":"Adomavicius, G., & Tuzhilin, A. (1999). User profiling in personalization applications through rule discovery and validation. Paper presented at the Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining.","DOI":"10.1145\/312129.312287"},{"issue":"3","key":"9690_CR2","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1006\/jpdc.2000.1693","volume":"61","author":"RC Agarwal","year":"2001","unstructured":"Agarwal, R. C., Aggarwal, C. C., & Prasad, V. V. V. (2001). A tree projection algorithm for generation of frequent item sets. Journal of Parallel and Distributed Computing, 61(3), 350\u2013371. doi: 10.1006\/jpdc.2000.1693 .","journal-title":"Journal of Parallel and Distributed Computing"},{"key":"9690_CR3","series-title":"Paper presented at the Proc. 20th Int","volume-title":"Fast algorithms for mining association rules","author":"R Agrawal","year":"1994","unstructured":"Agrawal, R., & Srikant, R. (1994). Fast algorithms for mining association rules, Paper presented at the Proc. 20th Int. VLDB: Conf. Very Large Data Bases."},{"key":"9690_CR4","volume-title":"Mining association rules between sets of items in large databases","author":"R Agrawal","year":"1993","unstructured":"Agrawal, R., Imieli\u0144ski, T., & Swami, A. (1993). Mining association rules between sets of items in large databases. Paper presented at the ACM SIGMOD Record."},{"issue":"6","key":"9690_CR5","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1016\/j.knosys.2009.06.004","volume":"22","author":"B Alatas","year":"2009","unstructured":"Alatas, B., & Akin, E. (2009). Multi-objective rule mining using a chaotic particle swarm optimization algorithm. Knowledge-Based Systems, 22(6), 455\u2013460. doi: 10.1016\/j.knosys.2009.06.004 .","journal-title":"Knowledge-Based Systems"},{"issue":"1","key":"9690_CR6","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1016\/j.asoc.2007.05.003","volume":"8","author":"B Alatas","year":"2008","unstructured":"Alatas, B., Akin, E., & Karci, A. (2008). MODENAR: Multi-objective differential evolution algorithm for mining numeric association rules. Applied Soft Computing, 8(1), 646\u2013656.","journal-title":"Applied Soft Computing"},{"issue":"3","key":"9690_CR7","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1007\/s00500-008-0323-y","volume":"13","author":"J Alcal\u00e1-Fdez","year":"2009","unstructured":"Alcal\u00e1-Fdez, J., S\u00e1nchez, L., Garc\u00eda, S., del Jes\u00fas, M. J., Ventura, S., Garrell, J., et al. (2009). KEEL: a software tool to assess evolutionary algorithms for data mining problems. Soft Computing, 13(3), 307\u2013318.","journal-title":"Soft Computing"},{"issue":"3","key":"9690_CR8","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1007\/s10844-007-0044-1","volume":"31","author":"R Alhajj","year":"2008","unstructured":"Alhajj, R., & Kaya, M. (2008). Multi-objective genetic algorithms based automated clustering for fuzzy association rules mining. Journal of Intelligent Information Systems, 31(3), 243\u2013264. doi: 10.1007\/s10844-007-0044-1 .","journal-title":"Journal of Intelligent Information Systems"},{"key":"9690_CR9","unstructured":"Alpaydin, E., & Kaynak, C. (1998). Optical Recognition of Handwritten Digits Data Set UCI repository of machine learning databases. Retrieved from http:\/\/www.cs.uci.edu\/~mlearn\/MLRepository.html"},{"key":"9690_CR10","volume-title":"Information Quality Measurement in Data Integration Schemas","author":"MDCM Batista","year":"2007","unstructured":"Batista, M. D. C. M., & Salgado, A. C. (2007). Information Quality Measurement in Data Integration Schemas. Paper presented at the QDB."},{"issue":"9","key":"9690_CR11","doi-asserted-by":"crossref","first-page":"4259","DOI":"10.1016\/j.eswa.2013.12.043","volume":"41","author":"V Beiranvand","year":"2014","unstructured":"Beiranvand, V., Mobasher-Kashani, M., & Abu Bakar, A. (2014). Multi-objective PSO algorithm for mining numerical association rules without a priori discretization. Expert Systems with Applications, 41(9), 4259\u20134273.","journal-title":"Expert Systems with Applications"},{"issue":"7","key":"9690_CR12","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1016\/S0378-7206(02)00093-9","volume":"40","author":"E Bendoly","year":"2003","unstructured":"Bendoly, E. (2003). Theory and support for process frameworks of knowledge discovery and data mining from ERP systems. Information Management, 40(7), 639\u2013647.","journal-title":"Information Management"},{"issue":"3","key":"9690_CR13","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/S0378-7206(01)00091-X","volume":"39","author":"I Bose","year":"2001","unstructured":"Bose, I., & Mahapatra, R. K. (2001). Business data mining\u2014a machine learning perspective. Information Management, 39(3), 211\u2013225.","journal-title":"Information Management"},{"key":"9690_CR14","volume-title":"Dynamic itemset counting and implication rules for market basket data","author":"S Brin","year":"1997","unstructured":"Brin, S., Motwani, R., Ullman, J. D., & Tsur, S. (1997). Dynamic itemset counting and implication rules for market basket data. Paper presented at the ACM SIGMOD Record."},{"issue":"9","key":"9690_CR15","doi-asserted-by":"crossref","first-page":"2964","DOI":"10.1016\/j.cor.2007.01.005","volume":"35","author":"S Busygin","year":"2008","unstructured":"Busygin, S., Prokopyev, O., & Pardalos, P. M. (2008). Biclustering in data mining. Computers & Operations Research, 35(9), 2964\u20132987.","journal-title":"Computers & Operations Research"},{"key":"9690_CR16","unstructured":"Cabena, P., Hadjinian, P., Stadler, R., Verhees, J., Zanasi, A., I. B. M. C., &., I. T. S. O. (1998). Discovering data mining: from concept to implementation (Vol. 1): Prentice Hall Upper Saddle River, NJ."},{"key":"9690_CR17","doi-asserted-by":"publisher","unstructured":"Ceglar, A., & Roddick, J. F. (2006). Association mining. ACM Computing Surveys, 38(2). doi: 10.1145\/1132956\/1132958 .","DOI":"10.1145\/1132956\/1132958"},{"key":"9690_CR18","unstructured":"Chapman, P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C., & Wirth, R. (2000). CRISP-DM 1.0 Step-by-step data mining guide."},{"issue":"6","key":"9690_CR19","doi-asserted-by":"crossref","first-page":"866","DOI":"10.1109\/69.553155","volume":"8","author":"MS Chen","year":"1996","unstructured":"Chen, M. S., Han, J. W., & Yu, P. S. (1996). Data mining: An overview from a database perspective. IEEE Transactions on Knowledge and Data Engineering, 8(6), 866\u2013883.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"2","key":"9690_CR20","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1016\/j.dss.2005.03.005","volume":"42","author":"G Chen","year":"2006","unstructured":"Chen, G., Liu, H., Yu, L., Wei, Q., & Zhang, X. (2006). A new approach to classification based on association rule mining. Decision Support Systems, 42(2), 674\u2013689.","journal-title":"Decision Support Systems"},{"issue":"3","key":"9690_CR21","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1109\/TEVC.2004.826067","volume":"8","author":"CAC Coello","year":"2004","unstructured":"Coello, C. A. C., Pulido, G. T., & Lechuga, M. S. (2004). Handling multiple objectives with particle swarm optimization. Evolutionary Computation, IEEE Transactions on, 8(3), 256\u2013279.","journal-title":"Evolutionary Computation, IEEE Transactions on"},{"issue":"6","key":"9690_CR22","doi-asserted-by":"crossref","first-page":"774","DOI":"10.1109\/TKDE.2004.8","volume":"16","author":"F Coenen","year":"2004","unstructured":"Coenen, F., Leng, P., & Ahmed, S. (2004). Data structure for association rule mining: T-trees and P-trees. IEEE Transactions on Knowledge and Data Engineering, 16(6), 774\u2013778.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"3","key":"9690_CR23","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1016\/j.ejor.2012.03.039","volume":"221","author":"D Corne","year":"2012","unstructured":"Corne, D., Dhaenens, C., & Jourdan, L. (2012). Synergies between operations research and data mining: The emerging use of multi-objective approaches. European Journal of Operational Research, 221(3), 469\u2013479. doi: 10.1016\/j.ejor.2012.03.039 .","journal-title":"European Journal of Operational Research"},{"issue":"4","key":"9690_CR24","first-page":"216","volume":"38","author":"J Cui","year":"2011","unstructured":"Cui, J., Li, Q., & Yang, L.-P. (2011). Fast Algorithm for Mining Association Rules Based on Vertically Distributed Data in Large Dense Databases. Computer Science, 38(4), 216.","journal-title":"Computer Science"},{"issue":"2","key":"9690_CR25","first-page":"105","volume":"3","author":"S Das","year":"2009","unstructured":"Das, S., & Saha, B. (2009). Data Quality Mining using Genetic Algorithm. International Journal of Computer Science and Security, 3(2), 105\u2013112.","journal-title":"International Journal of Computer Science and Security"},{"issue":"2","key":"9690_CR26","doi-asserted-by":"crossref","first-page":"764","DOI":"10.1016\/j.ejor.2008.07.019","volume":"197","author":"I Davidson","year":"2009","unstructured":"Davidson, I., & Tayi, G. (2009). Data preparation using data quality matrices for classification mining. European Journal of Operational Research, 197(2), 764\u2013772.","journal-title":"European Journal of Operational Research"},{"issue":"4","key":"9690_CR27","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/S1568-4946(01)00024-2","volume":"1","author":"I De Falco","year":"2002","unstructured":"De Falco, I., Della Cioppa, A., & Tarantino, E. (2002). Discovering interesting classification rules with genetic programming. Applied Soft Computing, 1(4), 257\u2013269.","journal-title":"Applied Soft Computing"},{"issue":"3","key":"9690_CR28","doi-asserted-by":"publisher","first-page":"898","DOI":"10.1016\/j.ejor.2004.08.025","volume":"169","author":"B Iglesia de la","year":"2006","unstructured":"de la Iglesia, B., Richards, G., Philpott, M. S., & Rayward-Smith, V. J. (2006). The application and effectiveness of a multi-objective metaheuristic algorithm for partial classification. European Journal of Operational Research, 169(3), 898\u2013917. doi: 10.1016\/j.ejor.2004.08.025 .","journal-title":"European Journal of Operational Research"},{"issue":"2","key":"9690_CR29","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1109\/4235.996017","volume":"6","author":"K Deb","year":"2002","unstructured":"Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182\u2013197. doi: 10.1109\/4235.996017 .","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"1","key":"9690_CR30","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.swevo.2011.02.002","volume":"1","author":"J Derrac","year":"2011","unstructured":"Derrac, J., Garc\u00eda, S., Molina, D., & Herrera, F. (2011). A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm and Evolutionary Computation, 1(1), 3\u201318.","journal-title":"Swarm and Evolutionary Computation"},{"issue":"1","key":"9690_CR31","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1057\/ejis.2010.61","volume":"21","author":"N Evangelopoulos","year":"2010","unstructured":"Evangelopoulos, N., Zhang, X., & Prybutok, V. R. (2010). Latent Semantic Analysis: five methodological recommendations. European Journal of Information Systems, 21(1), 70\u201386. doi: 10.1057\/ejis.2010.61 .","journal-title":"European Journal of Information Systems"},{"issue":"11","key":"9690_CR32","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1145\/240455.240464","volume":"39","author":"U Fayyad","year":"1996","unstructured":"Fayyad, U., PiatetskyShapiro, G., & Smyth, P. (1996). The KDD process for extracting useful knowledge from volumes of data. Communications of the ACM, 39(11), 27\u201334. doi: 10.1145\/240455.240464 .","journal-title":"Communications of the ACM"},{"issue":"5","key":"9690_CR33","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/S0378-7206(99)00051-8","volume":"37","author":"A Feelders","year":"2000","unstructured":"Feelders, A., Daniels, H., & Holsheimer, M. (2000). Methodological and practical aspects of data mining. Information Management, 37(5), 271\u2013281.","journal-title":"Information Management"},{"key":"9690_CR34","doi-asserted-by":"crossref","unstructured":"Fidelis, M. V., Lopes, H., & Freitas, A. (2000). Discovering comprehensible classification rules with a genetic algorithm. Paper presented at the Evolutionary Computation, 2000. Proceedings of the 2000 Congress on.","DOI":"10.1109\/CEC.2000.870381"},{"issue":"2","key":"9690_CR35","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/S0378-7206(01)00083-0","volume":"39","author":"CW Fisher","year":"2001","unstructured":"Fisher, C. W., & Kingma, B. R. (2001). Criticality of data quality as exemplified in two disasters. Information Management, 39(2), 109\u2013116. doi: 10.1016\/S0378-7206(01)00083-0 .","journal-title":"Information Management"},{"key":"9690_CR36","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-662-04923-5","volume-title":"Data mining and knowledge discovery with evolutionary algorithms: Springer","author":"AA Freitas","year":"2002","unstructured":"Freitas, A. A. (2002). Data mining and knowledge discovery with evolutionary algorithms: Springer."},{"key":"9690_CR37","doi-asserted-by":"publisher","unstructured":"Geng, L. Q., & Hamilton, H. J. (2006). Interestingness measures for data mining: A survey. ACM Computing Surveys, 38(3). doi 10.1145\/1132960.1132963","DOI":"10.1145\/1132960.1132963"},{"issue":"1","key":"9690_CR38","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1023\/B:JIMS.0000010073.54241.e7","volume":"15","author":"C Gertosio","year":"2004","unstructured":"Gertosio, C., & Dussauchoy, A. (2004). Knowledge discovery from industrial databases. Journal of Intelligent Manufacturing, 15(1), 29\u201337.","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"1","key":"9690_CR39","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.ins.2003.03.021","volume":"163","author":"A Ghosh","year":"2004","unstructured":"Ghosh, A., & Nath, B. (2004). Multi-objective rule mining using genetic algorithms. Information Sciences, 163(1), 123\u2013133.","journal-title":"Information Sciences"},{"key":"9690_CR40","doi-asserted-by":"crossref","unstructured":"Gray, B., & Orlowska, M. E. (1998). CCAIIA: Clustering categorical attributes into interesting association rules. In: Pacific-Asia Conference on Knowledge Discovery and Data Mining (pp. 132\u2013143). Germany: Springer Berlin Heidelberg.","DOI":"10.1007\/3-540-64383-4_12"},{"issue":"3","key":"9690_CR41","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1007\/s10796-012-9401-x","volume":"15","author":"C Guerra-Garc\u00eda","year":"2013","unstructured":"Guerra-Garc\u00eda, C., Caballero, I., & Piattini, M. (2013). Capturing data quality requirements for web applications by means of DQ_WebRE. Information Systems Frontiers, 15(3), 433\u2013445.","journal-title":"Information Systems Frontiers"},{"key":"9690_CR42","unstructured":"Han, J., & Kamber, M. (2006). Data mining: concepts and techniques. San Francisco: Morgan Kaufmann Publishers Inc."},{"key":"9690_CR43","unstructured":"Hipp, J., Guntzer, U., & Grimmer, U. (2001). Data quality mining-making a virtue of necessity. Paper presented at the Workshop on Research Issues in Data Mining and Knowledge Discovery DMKD, Santa Barbara, CA, http:\/\/www.cs.cornell.edu\/johannes\/papers\/dmkd2001-papers\/p5_hipp.pdf."},{"key":"9690_CR44","unstructured":"Hofmann, H. (1994). Statlog (German Credit Data) Data Set UCI repository of machine learning databases. Retrieved from http:\/\/www.cs.uci.edu\/~mlearn\/MLRepository.html"},{"key":"9690_CR45","doi-asserted-by":"crossref","unstructured":"Houtsma, M., & Swami, A. (1995). Set-oriented mining for association rules in relational databases. Paper presented at the Data Engineering, 1995. Proceedings of the Eleventh International Conference on.","DOI":"10.1109\/ICDE.1995.380413"},{"issue":"1","key":"9690_CR46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0378-7206(00)00051-3","volume":"38","author":"SC Hui","year":"2000","unstructured":"Hui, S. C., & Jha, G. (2000). Data mining for customer service support. Information Management, 38(1), 1\u201313.","journal-title":"Information Management"},{"issue":"2","key":"9690_CR47","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1007\/s10796-012-9365-x","volume":"15","author":"NK Janjua","year":"2013","unstructured":"Janjua, N. K., Hussain, F. K., & Hussain, O. K. (2013). Semantic information and knowledge integration through argumentative reasoning to support intelligent decision making. Information Systems Frontiers, 15(2), 167\u2013192.","journal-title":"Information Systems Frontiers"},{"key":"9690_CR48","unstructured":"Karaboga, D. (2005). An idea based on honey bee swarm for numerical optimization. Techn. Rep. TR06, Erciyes Univ. Press, Erciyes."},{"issue":"1","key":"9690_CR49","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1016\/j.amc.2009.03.090","volume":"214","author":"D Karaboga","year":"2009","unstructured":"Karaboga, D., & Akay, B. (2009). A comparative study of Artificial Bee Colony algorithm. Applied Mathematics and Computation, 214(1), 108\u2013132. doi: 10.1016\/j.amc.2009.03.090 .","journal-title":"Applied Mathematics and Computation"},{"key":"9690_CR50","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1007\/978-3-540-72950-1_77","volume":"4529","author":"D Karaboga","year":"2007","unstructured":"Karaboga, D., & Basturk, B. (2007). Artificial Bee Colony (ABC) optimization algorithm for solving constrained optimization problems. Foundations of Fuzzy Logic and Soft Computing, Proceedings, 4529, 789\u2013798.","journal-title":"Foundations of Fuzzy Logic and Soft Computing, Proceedings"},{"issue":"1","key":"9690_CR51","doi-asserted-by":"publisher","first-page":"687","DOI":"10.1016\/j.asoc.2007.05.007","volume":"8","author":"D Karaboga","year":"2008","unstructured":"Karaboga, D., & Basturk, B. (2008). On the performance of artificial bee colony (ABC) algorithm. Applied Soft Computing, 8(1), 687\u2013697. doi: 10.1016\/j.asoc.2007.05.007 .","journal-title":"Applied Soft Computing"},{"issue":"2","key":"9690_CR52","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1007\/s00158-004-0465-1","volume":"29","author":"IY Kim","year":"2005","unstructured":"Kim, I. Y., & De Weck, O. (2005). Adaptive weighted-sum method for bi-objective optimization: Pareto front generation. Structural and Multidisciplinary Optimization, 29(2), 149\u2013158.","journal-title":"Structural and Multidisciplinary Optimization"},{"key":"9690_CR53","doi-asserted-by":"crossref","unstructured":"Klemettinen, M., Mannila, H., Ronkainen, P., Toivonen, H., & Verkamo, A. I. (1994). Finding interesting rules from large sets of discovered association rules. Paper presented at the Proceedings of the third international conference on Information and knowledge management.","DOI":"10.1145\/191246.191314"},{"issue":"11","key":"9690_CR54","doi-asserted-by":"crossref","first-page":"3136","DOI":"10.1016\/j.cor.2005.01.024","volume":"33","author":"JF Kros","year":"2006","unstructured":"Kros, J. F., Lin, M., & Brown, M. L. (2006). Effects of the neural network s-Sigmoid function on KDD in the presence of imprecise data. Computers & Operations Research, 33(11), 3136\u20133149.","journal-title":"Computers & Operations Research"},{"issue":"1","key":"9690_CR55","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1017\/S0269888906000738","volume":"21","author":"LA Kurgan","year":"2006","unstructured":"Kurgan, L. A., & Musilek, P. (2006). A survey of knowledge discovery and data mining process models. Knowledge Engineering Review, 21(1), 1\u201324. doi: 10.1017\/S0269888906000738 .","journal-title":"Knowledge Engineering Review"},{"issue":"1","key":"9690_CR56","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1287\/mnsc.1120.1578","volume":"59","author":"A Lahiri","year":"2013","unstructured":"Lahiri, A., & Dey, D. (2013). Effects of piracy on quality of information goods. Management Science, 59(1), 245\u2013264.","journal-title":"Management Science"},{"key":"9690_CR57","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/4037.001.0001","volume-title":"Journey to data quality","author":"YW Lee","year":"2006","unstructured":"Lee, Y. W. (2006). Journey to data quality. Cambridge: MIT Press."},{"issue":"1","key":"9690_CR58","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1007\/s10479-013-1482-5","volume":"211","author":"J Lee","year":"2013","unstructured":"Lee, J., & Pr\u00e9kopa, A. (2013). Properties and calculation of multivariate risk measures: MVaR and MCVaR. Annals of Operations Research, 211(1), 225\u2013254.","journal-title":"Annals of Operations Research"},{"issue":"5","key":"9690_CR59","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1016\/j.knosys.2007.01.002","volume":"20","author":"T Li","year":"2007","unstructured":"Li, T., Ruan, D., Geert, W., Song, J., & Xu, Y. (2007). A rough sets based characteristic relation approach for dynamic attribute generalization in data mining. Knowledge-Based Systems, 20(5), 485\u2013494.","journal-title":"Knowledge-Based Systems"},{"issue":"5","key":"9690_CR60","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1016\/S0378-7206(02)00062-9","volume":"40","author":"Q-Y Lin","year":"2003","unstructured":"Lin, Q.-Y., Chen, Y.-L., Chen, J.-S., & Chen, Y.-C. (2003). Mining inter-organizational retailing knowledge for an alliance formed by competitive firms. Information Management, 40(5), 431\u2013442.","journal-title":"Information Management"},{"issue":"3","key":"9690_CR61","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1016\/j.im.2004.01.008","volume":"42","author":"D-R Liu","year":"2005","unstructured":"Liu, D.-R., & Shih, Y.-Y. (2005). Integrating AHP and data mining for product recommendation based on customer lifetime value. Information Management, 42(3), 387\u2013400.","journal-title":"Information Management"},{"key":"9690_CR62","doi-asserted-by":"crossref","unstructured":"Lui, C.-L., & Chung, F.-L. (2000). Discovery of generalized association rules with multiple minimum supports Principles of Data Mining and Knowledge Discovery (pp. 510-515): Springer.","DOI":"10.1007\/3-540-45372-5_59"},{"issue":"2","key":"9690_CR63","doi-asserted-by":"publisher","first-page":"460","DOI":"10.1016\/j.datak.2005.10.001","volume":"59","author":"S Madnick","year":"2006","unstructured":"Madnick, S., & Zhu, H. (2006). Improving data quality through effective use of data semantics. Data & Knowledge Engineering, 59(2), 460\u2013475. doi: 10.1016\/j.datak.2005.10.001 .","journal-title":"Data & Knowledge Engineering"},{"key":"9690_CR64","unstructured":"Manyika, J., Institute, M. G., Chui, M., Brown, B., Bughin, J., Dobbs, R., Byers, A. H. (2011). Big data: The next frontier for innovation, competition, and productivity: McKinsey Global Institute."},{"issue":"2","key":"9690_CR65","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1017\/S0269888910000032","volume":"25","author":"G Mariscal","year":"2010","unstructured":"Mariscal, G., Marban, O., & Fernandez, C. (2010). A survey of data mining and knowledge discovery process models and methodologies. Knowledge Engineering Review, 25(2), 137\u2013166. doi: 10.1017\/S0269888910000032 .","journal-title":"Knowledge Engineering Review"},{"issue":"1\u20132","key":"9690_CR66","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1108\/02644401211206034","volume":"29","author":"MD Maximiano","year":"2012","unstructured":"Maximiano, M. D., Vega-Rodriguez, M. A., Gomez-Pulido, J. A., & Sanchez-Perez, J. M. (2012). Multiobjective metaheuristics for frequency assignment problem in mobile networks with large-scale real-world instances. Engineering Computations, 29(1\u20132), 144\u2013172. doi: 10.1108\/02644401211206034 .","journal-title":"Engineering Computations"},{"issue":"1","key":"9690_CR67","doi-asserted-by":"crossref","first-page":"60","DOI":"10.4156\/jcit.vol5.issue1.8","volume":"5","author":"M Nasiri","year":"2010","unstructured":"Nasiri, M., Taghavi, L. S., & Minaee, B. (2010). Multi-Objective Rule Mining using Simulated Annealing Algorithm. Journal of Convergence Information Technology, 5(1), 60\u201368.","journal-title":"Journal of Convergence Information Technology"},{"key":"9690_CR68","doi-asserted-by":"crossref","unstructured":"Noda, E., Freitas, A. A., & Lopes, H. S. (1999). Discovering interesting prediction rules with a genetic algorithm. Paper presented at the Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on.","DOI":"10.1109\/CEC.1999.782601"},{"issue":"7","key":"9690_CR69","doi-asserted-by":"publisher","first-page":"967","DOI":"10.1287\/mnsc.1040.0237","volume":"50","author":"A Parssian","year":"2004","unstructured":"Parssian, A., Sarkar, S., & Jacob, V. S. (2004). Assessing Data Quality for Information Products: Impact of Selection, Projection, and Cartesian Product. Management Science, 50(7), 967\u2013982. doi: 10.1287\/mnsc.1040.0237 .","journal-title":"Management Science"},{"issue":"5","key":"9690_CR70","first-page":"74","volume":"6","author":"G Piatetskyshapiro","year":"1991","unstructured":"Piatetskyshapiro, G. (1991). Knowledge Discovery in Databases. Ieee Expert-Intelligent Systems & Their Applications, 6(5), 74\u201376.","journal-title":"Ieee Expert-Intelligent Systems & Their Applications"},{"issue":"4","key":"9690_CR71","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1145\/505248.506010","volume":"45","author":"LL Pipino","year":"2002","unstructured":"Pipino, L. L., Lee, Y. W., & Wang, R. Y. (2002). Data quality assessment. Communications of the ACM, 45(4), 211. doi: 10.1145\/505248.506010 .","journal-title":"Communications of the ACM"},{"issue":"3","key":"9690_CR72","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1007\/s10796-013-9434-9","volume":"17","author":"T Popovic","year":"2015","unstructured":"Popovic, T., Kezunovic, M., & Krstajic, B. (2015). Smart grid data analytics for digital protective relay event recordings. Information Systems Frontiers, 17(3), 591\u2013600.","journal-title":"Information Systems Frontiers"},{"issue":"1","key":"9690_CR73","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.eswa.2010.06.060","volume":"38","author":"HR Qodmanan","year":"2011","unstructured":"Qodmanan, H. R., Nasiri, M., & Minaei-Bidgoli, B. (2011). Multi objective association rule mining with genetic algorithm without specifying minimum support and minimum confidence. Expert Systems with Applications, 38(1), 288\u2013298.","journal-title":"Expert Systems with Applications"},{"issue":"1","key":"9690_CR74","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1016\/j.datak.2007.05.006","volume":"64","author":"R Rak","year":"2008","unstructured":"Rak, R., Kurgan, L., & Reformat, M. (2008). A tree-projection-based algorithm for multi-label recurrent-item associative-classification rule generation. Data & Knowledge Engineering, 64(1), 171\u2013197. doi: 10.1016\/j.datak.2007.05.006 .","journal-title":"Data & Knowledge Engineering"},{"issue":"3","key":"9690_CR75","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1007\/s00500-008-0320-1","volume":"13","author":"AP Reynolds","year":"2009","unstructured":"Reynolds, A. P., & de la Iglesia, B. (2009). A multi-objective GRASP for partial classification. Soft Computing, 13(3), 227\u2013243. doi: 10.1007\/s00500-008-0320-1 .","journal-title":"Soft Computing"},{"key":"9690_CR76","doi-asserted-by":"crossref","unstructured":"Sheng, V. S., Provost, F., & Ipeirotis, P. G. (2008). Get another label? improving data quality and data mining using multiple, noisy labelers. Paper presented at the Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining.","DOI":"10.1145\/1401890.1401965"},{"issue":"2","key":"9690_CR77","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1016\/j.ejor.2006.02.040","volume":"180","author":"R Sikora","year":"2007","unstructured":"Sikora, R., & Piramuthu, S. (2007). Framework for efficient feature selection in genetic algorithm based data mining. European Journal of Operational Research, 180(2), 723\u2013737. doi: 10.1016\/j.ejor.2006.02.040 .","journal-title":"European Journal of Operational Research"},{"key":"9690_CR78","unstructured":"Soler, S. V., & Yankelevich, D. (2001). Quality Mining: A Data Mining Based Method for Data Quality Evaluation. Paper presented at the Processing of the Sixth international Conference on Data Quality, MIT."},{"issue":"3","key":"9690_CR79","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1007\/s10462-011-9212-3","volume":"36","author":"S Srinivasan","year":"2011","unstructured":"Srinivasan, S., & Ramakrishnan, S. (2011). Evolutionary multi objective optimization for rule mining: a review. Artificial Intelligence Review, 36(3), 205\u2013248. doi: 10.1007\/s10462-011-9212-3 .","journal-title":"Artificial Intelligence Review"},{"issue":"1","key":"9690_CR80","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.ejor.2011.06.006","volume":"215","author":"W Szeto","year":"2011","unstructured":"Szeto, W., Wu, Y., & Ho, S. C. (2011). An artificial bee colony algorithm for the capacitated vehicle routing problem. European Journal of Operational Research, 215(1), 126\u2013135.","journal-title":"European Journal of Operational Research"},{"key":"9690_CR81","unstructured":"Tan, P.-N., & Kumar, V. (2000). Interestingness measures for association patterns: A perspective. Paper presented at the Proc. of Workshop on Postprocessing in Machine Learning and Data Mining."},{"issue":"4","key":"9690_CR82","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1007\/s10618-013-0326-x","volume":"28","author":"C Tew","year":"2014","unstructured":"Tew, C., Giraud-Carrier, C., Tanner, K., & Burton, S. (2014). Behavior-based clustering and analysis of interestingness measures for association rule mining. Data Mining and Knowledge Discovery, 28(4), 1004\u20131045.","journal-title":"Data Mining and Knowledge Discovery"},{"key":"9690_CR83","doi-asserted-by":"crossref","unstructured":"Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 5\u201333.","DOI":"10.1080\/07421222.1996.11518099"},{"issue":"7","key":"9690_CR84","doi-asserted-by":"publisher","first-page":"985","DOI":"10.1109\/Tkde.2008.229","volume":"21","author":"K Wickramaratna","year":"2009","unstructured":"Wickramaratna, K., Kubat, M., & Premaratne, K. (2009). Predicting Missing Items in Shopping Carts. IEEE Transactions on Knowledge and Data Engineering, 21(7), 985\u2013998. doi: 10.1109\/Tkde.2008.229 .","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"7","key":"9690_CR85","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1016\/j.is.2003.12.003","volume":"29","author":"WE Winkler","year":"2004","unstructured":"Winkler, W. E. (2004). Methods for evaluating and creating data quality. Information Systems, 29(7), 531\u2013550.","journal-title":"Information Systems"},{"issue":"4","key":"9690_CR86","doi-asserted-by":"publisher","first-page":"597","DOI":"10.1142\/S0219622006002258","volume":"5","author":"Q Yang","year":"2006","unstructured":"Yang, Q., & Wu, X. D. (2006). 10 Challenging problems in data mining research. International Journal of Information Technology and Decision Making, 5(4), 597\u2013604. doi: 10.1142\/S0219622006002258 .","journal-title":"International Journal of Information Technology and Decision Making"},{"key":"9690_CR87","unstructured":"Zitzler, E., Laumanns, M., & Thiele, L. (2001). SPEA2: Improving the strength Pareto evolutionary algorithm: Eidgen\u00f6ssische Technische Hochschule Z\u00fcrich (ETH), Institut f\u00fcr Technische Informatik und Kommunikationsnetze (TIK)."}],"container-title":["Information Systems Frontiers"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10796-016-9690-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10796-016-9690-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10796-016-9690-6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10796-016-9690-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T19:02:26Z","timestamp":1749063746000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10796-016-9690-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,8,18]]},"references-count":87,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2018,4]]}},"alternative-id":["9690"],"URL":"https:\/\/doi.org\/10.1007\/s10796-016-9690-6","relation":{},"ISSN":["1387-3326","1572-9419"],"issn-type":[{"type":"print","value":"1387-3326"},{"type":"electronic","value":"1572-9419"}],"subject":[],"published":{"date-parts":[[2016,8,18]]}}}