{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T18:01:59Z","timestamp":1765994519683,"version":"build-2065373602"},"reference-count":75,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2018,8,20]],"date-time":"2018-08-20T00:00:00Z","timestamp":1534723200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>The paper discusses the use of parallel computation to obtain rough set approximations from large-scale information systems where missing data exist in both condition and decision attributes. To date, many studies have focused on missing condition data, but very few have accounted for missing decision data, especially in enlarging datasets. One of the approaches for dealing with missing data in condition attributes is named twofold rough approximations. The paper aims to extend the approach to deal with missing data in the decision attribute. In addition, computing twofold rough approximations is very intensive, thus the approach is not suitable when input datasets are large. We propose parallel algorithms to compute twofold rough approximations in large-scale datasets. Our method is based on MapReduce, a distributed programming model for processing large-scale data. We introduce the original sequential algorithm first and then the parallel version is introduced. Comparison between the two approaches through experiments shows that our proposed parallel algorithms are suitable for and perform efficiently on large-scale datasets that have missing data in condition and decision attributes.<\/jats:p>","DOI":"10.3390\/computers7030044","type":"journal-article","created":{"date-parts":[[2018,8,20]],"date-time":"2018-08-20T11:23:06Z","timestamp":1534764186000},"page":"44","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Parallel Computation of Rough Set Approximations in Information Systems with Missing Decision Data"],"prefix":"10.3390","volume":"7","author":[{"given":"Thinh","family":"Cao","sequence":"first","affiliation":[{"name":"Information Science and Control Engineering, Nagaoka University of Technology, Nagaoka 9402137, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Koichi","family":"Yamada","sequence":"additional","affiliation":[{"name":"Information Science and Control Engineering, Nagaoka University of Technology, Nagaoka 9402137, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muneyuki","family":"Unehara","sequence":"additional","affiliation":[{"name":"Information Science and Control Engineering, Nagaoka University of Technology, Nagaoka 9402137, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Izumi","family":"Suzuki","sequence":"additional","affiliation":[{"name":"Information Science and Control Engineering, Nagaoka University of Technology, Nagaoka 9402137, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9992-2974","authenticated-orcid":false,"given":"Do Van","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Human Machine Interaction Laboratory, UET, Vietnam National University, Hanoi 10000, Vietnam"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1007\/BF01001956","article-title":"Rough sets","volume":"Volume 11","author":"Pawlak","year":"1982","journal-title":"International Journal of Computer and Information Sciences"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Pawlak, Z. (1991). Rough Sets. Theoretical Aspects of Reasoning Data, Kluwer Acad.","DOI":"10.1007\/978-94-011-3534-4"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.ins.2016.05.025","article-title":"Cost-sensitive feature selection based on adaptive neighborhood granularity with multi-level confidence","volume":"366","author":"Zhao","year":"2016","journal-title":"Inf. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.knosys.2017.02.019","article-title":"Cost-sensitive rough set: A multi-granulation approach","volume":"123","author":"Ju","year":"2017","journal-title":"Knowl. Based Syst."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1109\/TKDE.2012.146","article-title":"A Group Incremental Approach to Feature Selection Applying Rough Set Technique","volume":"26","author":"Liang","year":"2014","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1016\/j.ins.2017.08.038","article-title":"Class-specific attribute reducts in rough set theory","volume":"418\u2013419","author":"Yao","year":"2017","journal-title":"Inf. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Roy, J., Adhikary, K., Kar, S., and Pamucar, D. (2018). A rough strength relational DEMATEL model for analysing the key success factors of hospital service quality. Decision Making: Applications in Management and Engineering, Electrocore.","DOI":"10.31181\/dmame1801121r"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1016\/S0377-2217(01)00259-4","article-title":"Economic and financial prediction using rough sets model","volume":"141","author":"Tay","year":"2002","journal-title":"Eur. J. Oper. Res."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1016\/S0261-5177(03)00009-8","article-title":"Incorporating the rough sets theory into travel demand analysis","volume":"24","author":"Goh","year":"2003","journal-title":"Tour. Manag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"902","DOI":"10.1587\/transinf.2014EDP7283","article-title":"Social network and tag sources based augmenting collaborative recommender system","volume":"E98D","author":"Ma","year":"2015","journal-title":"IEICE Trans. Inf. Syst."},{"key":"ref_11","first-page":"97","article-title":"A multi-criteria decision-making (MCDM) model in the security forces operations based on rough sets","volume":"Volume 1","author":"Karavidic","year":"2018","journal-title":"Decision Making: Applications in Management and Engineering"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1016\/S0167-8655(02)00196-4","article-title":"Rough set methods in feature selection and recognition","volume":"24","author":"Swiniarski","year":"2003","journal-title":"Pattern Recognit. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1109\/TKDE.2009.114","article-title":"Ensemble rough hypercuboid approach for classifying cancers","volume":"22","author":"Wei","year":"2010","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"904","DOI":"10.1016\/j.ejor.2015.08.053","article-title":"Two Bayesian approaches to rough sets","volume":"251","author":"Yao","year":"2016","journal-title":"Eur. J. Oper. Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1007\/s12559-016-9397-5","article-title":"Three-Way Decisions and Cognitive Computing","volume":"8","author":"Yao","year":"2016","journal-title":"Cognit. Comput."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.knosys.2015.01.004","article-title":"The two sides of the theory of rough sets","volume":"80","author":"Yao","year":"2015","journal-title":"Knowl. Based Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.ijar.2013.02.013","article-title":"Incorporating logistic regression to decision-theoretic rough sets for classifications","volume":"55","author":"Liu","year":"2014","journal-title":"Int. J. Approx. Reason."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ijar.2017.05.001","article-title":"A three-way decisions model with probabilistic rough sets for stream computing","volume":"88","author":"Xu","year":"2017","journal-title":"Int. J. Approx. Reason."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1016\/j.ins.2016.07.008","article-title":"A novel attribute reduction approach for multi-label data based on rough set theory","volume":"367","author":"Li","year":"2016","journal-title":"Inf. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"961","DOI":"10.3233\/IFS-141378","article-title":"Image Segmentation by Generalized Hierarchical Fuzzy C-means Algorithm","volume":"28","author":"Zheng","year":"2015","journal-title":"J. Intell. Fuzzy Syst."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1023\/A:1008384328214","article-title":"Data mining and machine oriented modeling: A granular computing approach","volume":"13","author":"Lin","year":"2000","journal-title":"Appl. Intell."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Cao, T., Yamada, K., Unehara, M., Suzuki, I., and Nguyen, D.V. (2016, January 24\u201329). Semi-supervised based rough set to handle missing decision data. Proceedings of the 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE, Vancouver, BC, Canada.","DOI":"10.1109\/FUZZ-IEEE.2016.7737930"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1221","DOI":"10.20965\/jaciii.2017.p1221","article-title":"Rough Set Model in Incomplete Decision Systems","volume":"21","author":"Cao","year":"2017","journal-title":"J. Adv. Comput. Intell. Intell. Inform."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1007\/s13042-015-0477-8","article-title":"Incremental method of updating approximations in DRSA under variations of multiple objects","volume":"9","author":"Li","year":"2018","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/j.ins.2011.12.036","article-title":"A parallel method for computing rough set approximations","volume":"194","author":"Zhang","year":"2012","journal-title":"Inf. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1016\/j.ijar.2013.08.003","article-title":"A comparison of parallel large-scale knowledge acquisition using rough set theory on different MapReduce runtime systems","volume":"55","author":"Zhang","year":"2014","journal-title":"Int. J. Approx. Reason."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/j.ins.2016.09.012","article-title":"Parallel attribute reduction in dominance-based neighborhood rough set","volume":"373","author":"Chen","year":"2016","journal-title":"Inf. Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.knosys.2015.05.003","article-title":"Parallel computing of approximations in dominance-based rough sets approach","volume":"87","author":"Li","year":"2015","journal-title":"Knowl. Based Syst."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1016\/j.ins.2014.04.019","article-title":"Parallel attribute reduction algorithms using MapReduce","volume":"279","author":"Qian","year":"2014","journal-title":"Inf. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.knosys.2014.09.001","article-title":"Hierarchical attribute reduction algorithms for big data using MapReduce","volume":"73","author":"Qian","year":"2015","journal-title":"Knowl. Based Syst."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1016\/j.ins.2014.09.056","article-title":"Incremental update of approximations in dominance-based rough sets approach under the variation of attribute values","volume":"294","author":"Li","year":"2015","journal-title":"Inf. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1764","DOI":"10.1016\/j.ijar.2014.05.009","article-title":"A rough set-based incremental approach for learning knowledge in dynamic incomplete information systems","volume":"55","author":"Liu","year":"2014","journal-title":"Int. J. Approx. Reason."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3890","DOI":"10.1016\/j.patcog.2014.06.002","article-title":"Incremental feature selection based on rough set in dynamic incomplete data","volume":"47","author":"Shu","year":"2014","journal-title":"Pattern Recognit."},{"key":"ref_34","unstructured":"Hu, J., Li, T., Luo, C., and Li, S. (2015, January 2\u20135). Incremental fuzzy probabilistic rough sets over dual universes. Proceedings of the 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Istanbul, Turkey."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Jin, Y., Li, Y., and He, Q. (2016, January 10\u201313). A fast positive-region reduction method based on dominance-equivalence relations. Proceedings of the 2016 International Conference on Machine Learning and Cybernetics (ICMLC), Jeju Island, South Korea.","DOI":"10.1109\/ICMLC.2016.7860893"},{"key":"ref_36","unstructured":"Dean, J., and Ghemawat, S. (2004, January 6\u20138). MapReduce: Simplified data processing on large clusters. Proceedings of the 6th conference on Symposium on Operating Systems Design and Implementation, San Francisco, CA, USA."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"546","DOI":"10.1080\/17451000.2013.798898","article-title":"Twofold rough approximations under incomplete information","volume":"42","author":"Nakata","year":"2013","journal-title":"Int. J. Gen. Syst."},{"key":"ref_38","unstructured":"Slezak, D., and Ziarko, W. (2002, January 9). Bayesian rough set model. Proceedings of the International Workshop on Foundation of Data Mining (FDM2002), Maebashi, Japan."},{"key":"ref_39","first-page":"372091","article-title":"Extended tolerance relation to define a new rough set model in incomplete information systems","volume":"2013","author":"Yamada","year":"2013","journal-title":"Adv. Fuzzy Syst."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"280","DOI":"10.20965\/jaciii.2014.p0280","article-title":"Rough set approach with imperfect data based on Dempster-Shafer theory","volume":"18","author":"Yamada","year":"2014","journal-title":"J. Adv. Comput. Intell. Intell. Inform."},{"key":"ref_41","first-page":"368","article-title":"On the unknown attribute values in learning from examples","volume":"Volume 542","author":"Ras","year":"1991","journal-title":"Methodologies for Intelligent Systems"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1007\/3-540-45554-X_46","article-title":"A comparison of several approaches to missing attribute values in data mining","volume":"Volume 2005","author":"Ziarko","year":"2001","journal-title":"Rough Sets and Current Trends in Computing"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Grzymala-Busse, J. (2004, January 1\u20135). Characteristic relations for incomplete data: A generalization of the indiscernibility relation. Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing, Uppsala, Sweden.","DOI":"10.1007\/978-3-540-25929-9_29"},{"key":"ref_44","first-page":"139","article-title":"Three approaches to missing attribute values: A rough set perspective","volume":"Volume 118","author":"Lin","year":"2008","journal-title":"Data Mining: Foundations and Practice"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1007\/978-3-642-11479-3_2","article-title":"Definability and other properties of approximations for generalized indiscernibility relations","volume":"Volume 5946","author":"Peters","year":"2010","journal-title":"Transactions on Rough Sets XI"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.ins.2012.01.009","article-title":"Generalized approximations defined by non-equivalence relations","volume":"193","author":"Guan","year":"2012","journal-title":"Inf. Sci."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Stefanowski, J., and Tsoukias, A. (1999, January 11\u201319). On the extension of rough sets under incomplete information. Proceedings of the New directions in rough sets, data mining and granular-soft computing, Yamaguchi, Japan.","DOI":"10.1007\/978-3-540-48061-7_11"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1111\/0824-7935.00162","article-title":"Incomplete information tables and rough classication","volume":"17","author":"Stefanowski","year":"2001","journal-title":"Comput. Intell."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Katzberg, J.D., and Ziarko, W. (1993, January 12\u201315). Variable precision rough sets with asymmetric bounds. Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery, Banff, AB, Canada.","DOI":"10.1007\/978-1-4471-3238-7_21"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/S0020-0255(98)10019-1","article-title":"Rough set approach to incomplete information systems","volume":"112","author":"Kryszkiewicz","year":"1998","journal-title":"Inf. Sci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/S0020-0255(98)10065-8","article-title":"Rules in incomplete information systems","volume":"113","author":"Kryszkiewicz","year":"1999","journal-title":"Inf. Sci."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/S0020-0255(03)00061-6","article-title":"Maximal consistent block technique for rule acquisition in incomplete information systems","volume":"153","author":"Leung","year":"2003","journal-title":"Inf. Sci."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.ejor.2004.03.032","article-title":"Knowledge acquisition in incomplete information systems: A rough set approach","volume":"168","author":"Leung","year":"2006","journal-title":"Eur. J. Oper. Res."},{"key":"ref_54","unstructured":"Nakata, M., and Sakai, H. (2007, January 29\u201331). Handling missing values in terms of rough sets. Proceedings of the 23rd Fuzzy System Symposium, Nayoga, Japan."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"4140","DOI":"10.1016\/j.ins.2009.08.020","article-title":"Relative reducts in consistent and inconsistent decision tables of the Pawlak rough set model","volume":"179","author":"Miao","year":"2009","journal-title":"Inf. Sci."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1007\/3-540-39205-X_46","article-title":"Variable precision bayesian rough set model","volume":"2639","author":"Slezak","year":"2003","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/S1571-0661(04)80724-2","article-title":"Attribute reduction in the Bayesian version of variable precision rough set model","volume":"82","author":"Slezak","year":"2003","journal-title":"Electron. Notes Theor. Comput. Sci."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.ijar.2004.11.004","article-title":"The investigation of the Bayesian rough set model","volume":"40","author":"Slezak","year":"2005","journal-title":"Int. J. Approx. Reason."},{"key":"ref_59","unstructured":"Wang, G. (2002, January 12\u201317). Extension of rough set under incomplete information systems. Proceedings of the 2002 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE\u201902, Honolulu, Hawaii."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1142\/S0218488509006194","article-title":"Difference relation-based rough set and negative rules in incomplete information system","volume":"17","author":"Yang","year":"2009","journal-title":"Int. J. Uncertain. Fuzz. Knowl. Based Syst."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Yang, X., and Yang, J. (2012). Incomplete Information System and Rough Set Theory, Springer. [1st ed.].","DOI":"10.1007\/978-3-642-25935-7"},{"key":"ref_62","first-page":"58","article-title":"Prediction of missing values for decision attribute","volume":"4","author":"Medhat","year":"2012","journal-title":"J. Inform. Technol. Comput. Sci."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.simpat.2016.01.010","article-title":"Towards scalable rough set based attribute subset selection for intrusion detection using parallel genetic algorithm in MapReduce","volume":"64","author":"Alshammari","year":"2016","journal-title":"Simul. Model. Pract. Theory"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Verma, A., Llora, X., Goldberg, D.E., and Campbell, R.H. (December, January 30). Scaling Genetic Algorithms Using MapReduce. Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications, Pisa, Italy.","DOI":"10.1109\/ISDA.2009.181"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.parco.2011.02.006","article-title":"A generic parallel processing model for facilitating data mining and integration","volume":"37","author":"Han","year":"2011","journal-title":"Parallel Comput."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"McNabb, A.W., Monson, C.K., and Seppi, K.D. (2007, January 25\u201328). Parallel PSO using MapReduce. Proceedings of the 2007 IEEE Congress on Evolutionary Computation, Singapore.","DOI":"10.1109\/CEC.2007.4424448"},{"key":"ref_67","unstructured":"Chu, C.T., Kim, S.K., Lin, Y.A., Yu, Y., Bradski, G., Ng, A.Y., and Olukotun, K. (2012, January 12\u201315). Map-reduce for Machine Learning on Multicore. Proceedings of the 19th International Conference on Neural Information Processing Systems, Doha, Qatar."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s10994-011-5245-8","article-title":"Data and task parallelism in ILP using MapReduce","volume":"86","author":"Srinivasan","year":"2012","journal-title":"Mach. Learn."},{"key":"ref_69","unstructured":"Jaatun, M.G., Zhao, G., and Rong, C. (2009). Parallel K-Means Clustering Based on MapReduce. Cloud Computing, Springer."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/j.jcss.2009.11.006","article-title":"Parallelizing XML data-streaming workflows via MapReduce","volume":"76","author":"Zinn","year":"2010","journal-title":"J. Comput. Syst. Sci."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Li, P., Wu, J., and Shang, L. (2013). Fast approximate attribute reduction with MapReduce. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer.","DOI":"10.1007\/978-3-642-41299-8_26"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1109\/TKDE.2014.2330821","article-title":"A Parallel Matrix-Based Method for Computing Approximations in Incomplete Information Systems","volume":"27","author":"Zhang","year":"2015","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/j.knosys.2017.06.027","article-title":"Complete tolerance relation based parallel filling for incomplete energy big data","volume":"132","author":"Yuan","year":"2017","journal-title":"Knowl. Based Syst."},{"key":"ref_74","unstructured":"Data, K.C. (2018, August 18). KDD Cup 1999 Data. Available online: http:\/\/kdd.ics.uci.edu\/databases\/kddcup99\/kddcup99.html."},{"key":"ref_75","unstructured":"(2018, August 18). Sourcecode. Available online: https:\/\/github.com\/KennyThinh\/ParallelComputationTwoFoldRS."}],"container-title":["Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-431X\/7\/3\/44\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:19:44Z","timestamp":1760195984000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-431X\/7\/3\/44"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,20]]},"references-count":75,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2018,9]]}},"alternative-id":["computers7030044"],"URL":"https:\/\/doi.org\/10.3390\/computers7030044","relation":{},"ISSN":["2073-431X"],"issn-type":[{"type":"electronic","value":"2073-431X"}],"subject":[],"published":{"date-parts":[[2018,8,20]]}}}