{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T20:57:31Z","timestamp":1761253051463,"version":"3.41.0"},"reference-count":50,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2016,2,8]],"date-time":"2016-02-08T00:00:00Z","timestamp":1454889600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100003621","name":"Ministry of Science, ICT and Future Planning","doi-asserted-by":"publisher","award":["IITP-2015-H8501-15-1013,No.2013R1A2A2A01068923"],"award-info":[{"award-number":["IITP-2015-H8501-15-1013,No.2013R1A2A2A01068923"]}],"id":[{"id":"10.13039\/501100003621","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Inf. Syst."],"published-print":{"date-parts":[[2016,4,20]]},"abstract":"<jats:p>\n            In electricity customer classification, the most important task is to avoid the curse of dimensionality problem, as the consumption diagrams have a large number of dimensions. To avoid the curse of dimensionality problem,\n            <jats:italic>field indices<\/jats:italic>\n            (load shape factor) are often used instead of consumption diagrams. Field indices are directly extracted from consumption diagrams according to a predefined formula. Previous studies show that the most important thing for defining such a formula is to find meaningful time intervals from consumption diagrams. However, the inconvenient thing is that there are still a lack of details to explain how to define such time intervals.\n          <\/jats:p>\n          <jats:p>\n            In our study, we propose a data mining--based method named\n            <jats:italic>SFATIE<\/jats:italic>\n            to support the extraction of field indices. The performance of the proposed method is evaluated by comparing it with other dimensionality reduction methods during the classification. For the classification, most often we have used classification methods like C5.0, SVM, Neural Net, Bayes Net, and Logistic. The experimental results show that our method is better or close to other dimensionality reduction methods. In addition, the experimental results show that our proposed method can produce the good quality of field indices and that these indices can improve the performance of electricity customer classification.\n          <\/jats:p>","DOI":"10.1145\/2858657","type":"journal-article","created":{"date-parts":[[2016,2,8]],"date-time":"2016-02-08T22:37:07Z","timestamp":1454971027000},"page":"1-18","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Subspace Frequency Analysis--Based Field Indices Extraction for Electricity Customer Classification"],"prefix":"10.1145","volume":"34","author":[{"given":"Minghao","family":"Piao","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Dongguk University Gyeongju Campus, Gyeongju, South Korea"}]},{"given":"Keun Ho","family":"Ryu","sequence":"additional","affiliation":[{"name":"School of Electrical and Computer Engineering, Chungbuk National University, Cheongju, South Korea"}]}],"member":"320","published-online":{"date-parts":[[2016,2,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/304181.304188"},{"volume-title":"Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications","author":"Agrawal Rakesh","key":"e_1_2_1_2_1","unstructured":"Rakesh Agrawal , Johannes Gehrke , Dimitrios Gunopulos , and Prabhakar Raghavan . 1998. Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications . Vol. 27 . ACM , New York, NY . Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, and Prabhakar Raghavan. 1998. Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications. Vol. 27. ACM, New York, NY."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.46"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2422531.2422562"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487166.2487175"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-012-0487-8"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2005.08.017"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1961189.1961199"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/59.627886"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/FSKD.2009.487"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2006.873122"},{"key":"e_1_2_1_12_1","volume-title":"Proceedings of the Telmark Discussion Forum. 2--4.","author":"Chicco Gianfranco","year":"2002","unstructured":"Gianfranco Chicco , Roberto Napoli , Federico Piglione , Petru Postolache , Mircea Scutariu , and Cornel Toader . 2002 . A review of concepts and techniques for emergent customer categorisation . In Proceedings of the Telmark Discussion Forum. 2--4. Gianfranco Chicco, Roberto Napoli, Federico Piglione, Petru Postolache, Mircea Scutariu, and Cornel Toader. 2002. A review of concepts and techniques for emergent customer categorisation. In Proceedings of the Telmark Discussion Forum. 2--4."},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1049\/ip-gtd:20041243"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/PTC.2001.964627"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2002.807085"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.2307\/353415"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.2829282"},{"key":"e_1_2_1_18_1","unstructured":"M. Ernoult and F. Meslier. 1982. Analysis and forecast of electrical energy demand. Revue G\u00e9n\u00e9rale de \u0142\u2019\u00c9lectricit\u00e9 4 381--387.  M. Ernoult and F. Meslier. 1982. Analysis and forecast of electrical energy demand. Revue G\u00e9n\u00e9rale de \u0142\u2019\u00c9lectricit\u00e9 4 381--387."},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2005.846234"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1012487302797"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/1656274.1656278"},{"volume-title":"A Tutorial on Learning with Bayesian Networks","author":"Heckerman David","key":"e_1_2_1_23_1","unstructured":"David Heckerman . 1998. A Tutorial on Learning with Bayesian Networks . Springer . David Heckerman. 1998. A Tutorial on Learning with Bayesian Networks. Springer."},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.3390\/en5125215"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2011.2177870"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/2.485891"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972740.23"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2005.5"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.5555\/2037010.2037058"},{"key":"e_1_2_1_30_1","volume-title":"Proceedings of the 9th International Conference on Industrial and Engineering Applications of AI and ES (ICML\u201996)","volume":"96","author":"Liu Huan","year":"1996","unstructured":"Huan Liu and Rudy Setiono . 1996 . A probabilistic approach to feature selection\u2014a filter solution . In Proceedings of the 9th International Conference on Industrial and Engineering Applications of AI and ES (ICML\u201996) , Vol. 96 . 319--327. Huan Liu and Rudy Setiono. 1996. A probabilistic approach to feature selection\u2014a filter solution. In Proceedings of the 9th International Conference on Industrial and Engineering Applications of AI and ES (ICML\u201996), Vol. 96. 319--327."},{"volume-title":"Proceedings of the 5th International Conference on the European Electricity Market (EEM\u201908)","author":"L\u00f3pez Jos\u00e9 J.","key":"e_1_2_1_31_1","unstructured":"Jos\u00e9 J. L\u00f3pez , Jos\u00e9 A. Aguado , Francisco Mart\u00edn , F. Munoz , Alejandro Rodr\u00edguez , and Jos\u00e9 E. Ruiz . 2008. Electric customer classification using Nopfield recurrent ANN . In Proceedings of the 5th International Conference on the European Electricity Market (EEM\u201908) . IEEE, Los Alamitos, CA, 1--6. Jos\u00e9 J. L\u00f3pez, Jos\u00e9 A. Aguado, Francisco Mart\u00edn, F. Munoz, Alejandro Rodr\u00edguez, and Jos\u00e9 E. Ruiz. 2008. Electric customer classification using Nopfield recurrent ANN. In Proceedings of the 5th International Conference on the European Electricity Market (EEM\u201908). IEEE, Los Alamitos, CA, 1--6."},{"key":"e_1_2_1_32_1","doi-asserted-by":"crossref","unstructured":"F. Mart\u00ednez-\u00c1lvarez A. Troncoso J. C. Riquelme and J. M. Riquelme. 2007. Partitioning-clustering techniques applied to the electricity price time series. In Intelligent Data Engineering and Automated Learning-IDEAL 2007. Springer 990--999.   F. Mart\u00ednez-\u00c1lvarez A. Troncoso J. C. Riquelme and J. M. Riquelme. 2007. Partitioning-clustering techniques applied to the electricity price time series. In Intelligent Data Engineering and Automated Learning-IDEAL 2007. Springer 990--999.","DOI":"10.1007\/978-3-540-77226-2_99"},{"volume-title":"Mathematical Classification and Clustering: From How to What and Why","author":"Mirkin Boris","key":"e_1_2_1_33_1","unstructured":"Boris Mirkin . 1998. Mathematical Classification and Clustering: From How to What and Why . Springer . Boris Mirkin. 1998. Mathematical Classification and Clustering: From How to What and Why. Springer."},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401956"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2006.123"},{"volume-title":"Proceedings of the 1st Open Source in Data Mining Workshop in Conjunction with the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (OSDM\/PAKDD\u201909)","author":"M\u00fcller E.","key":"e_1_2_1_36_1","unstructured":"E. M\u00fcller , I. Assent , S. G\u00fcnnemann , T. Jansen , and T. Seidl . 2009a. OpenSubspace: An open source framework for evaluation and exploration of subspace clustering algorithms in WEKA . In Proceedings of the 1st Open Source in Data Mining Workshop in Conjunction with the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (OSDM\/PAKDD\u201909) . 2--13. E. M\u00fcller, I. Assent, S. G\u00fcnnemann, T. Jansen, and T. Seidl. 2009a. OpenSubspace: An open source framework for evaluation and exploration of subspace clustering algorithms in WEKA. In Proceedings of the 1st Open Source in Data Mining Workshop in Conjunction with the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (OSDM\/PAKDD\u201909). 2--13."},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687627.1687770"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRD.2011.2142198"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2002.1033770"},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/1007730.1007731"},{"key":"e_1_2_1_41_1","volume-title":"Jin Hyoung Park, and Keun Ho Ryu.","author":"Piao Minghao","year":"2008","unstructured":"Minghao Piao , Heon Gyu Lee , Jin Hyoung Park, and Keun Ho Ryu. 2008 . Application of classification methods for forecasting mid-term power load patterns. In Advanced Intelligent Computing Theories and Applications: With Aspects of Contemporary Intelligent Computing Techniques. Springer , 47--54. Minghao Piao, Heon Gyu Lee, Jin Hyoung Park, and Keun Ho Ryu. 2008. Application of classification methods for forecasting mid-term power load patterns. In Advanced Intelligent Computing Theories and Applications: With Aspects of Contemporary Intelligent Computing Techniques. Springer, 47--54."},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/CIT.2010.503"},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2014.2309697"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/564691.564739"},{"key":"e_1_2_1_45_1","volume-title":"Data Mining Tools See5 and C5.0. Retrieved","author":"Quinlan Ross","year":"2016","unstructured":"Ross Quinlan . 2012. Data Mining Tools See5 and C5.0. Retrieved January 5, 2016 , from http:\/\/www.rulequest.com\/see5-info.html. Ross Quinlan. 2012. Data Mining Tools See5 and C5.0. Retrieved January 5, 2016, from http:\/\/www.rulequest.com\/see5-info.html."},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.5555\/1032649.1033453"},{"key":"e_1_2_1_47_1","first-page":"5","article-title":"Tariff development for consumer groups in internal European electricity markets. In Proceedings of the 16th International Conference and Exhibition on Electricity Distribution","volume":"5","author":"Stephenson P.","year":"2001","unstructured":"P. Stephenson , I. Lungu , M. Paun , I. Silvas , and G. Tupu . 2001 . Tariff development for consumer groups in internal European electricity markets. In Proceedings of the 16th International Conference and Exhibition on Electricity Distribution . Part 1: Contributions , Vol. 5. 5 . P. Stephenson, I. Lungu, M. Paun, I. Silvas, and G. Tupu. 2001. Tariff development for consumer groups in internal European electricity markets. In Proceedings of the 16th International Conference and Exhibition on Electricity Distribution. Part 1: Contributions, Vol. 5. 5.","journal-title":"Part 1: Contributions"},{"key":"e_1_2_1_48_1","unstructured":"Pang-Ning Tan Michael Steinbach and Vipin Kumar. 2007. Introduction to Data Mining. Pearson Education India.  Pang-Ning Tan Michael Steinbach and Vipin Kumar. 2007. Introduction to Data Mining. Pearson Education India."},{"volume-title":"Proceedings of the IEEE Power Systems Conference and Exposition. IEEE","author":"Verd\u00fa S. V.","key":"e_1_2_1_49_1","unstructured":"S. V. Verd\u00fa , M. O. Garc\u00eda , F. J. Garc\u00eda Franco , N. Encinas , A. G. Marin , A. Molina , and E. G. Lazaro . 2004. Characterization and identification of electrical customers through the use of self-organizing maps and daily load parameters . In Proceedings of the IEEE Power Systems Conference and Exposition. IEEE , Los Alamitos, CA, 899--906. S. V. Verd\u00fa, M. O. Garc\u00eda, F. J. Garc\u00eda Franco, N. Encinas, A. G. Marin, A. Molina, and E. G. Lazaro. 2004. Characterization and identification of electrical customers through the use of self-organizing maps and daily load parameters. In Proceedings of the IEEE Power Systems Conference and Exposition. IEEE, Los Alamitos, CA, 899--906."},{"key":"e_1_2_1_50_1","volume-title":"Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM\u201903)","author":"Yiu Man Lung","year":"2003","unstructured":"Man Lung Yiu and Nikos Mamoulis . 2003 . Frequent-pattern based iterative projected clustering . In Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM\u201903) . IEEE, Los Alamitos, CA, 689--692. Man Lung Yiu and Nikos Mamoulis. 2003. Frequent-pattern based iterative projected clustering. In Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM\u201903). IEEE, Los Alamitos, CA, 689--692."},{"key":"e_1_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2011.2167524"}],"container-title":["ACM Transactions on Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2858657","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2858657","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T05:48:43Z","timestamp":1750225723000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2858657"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,2,8]]},"references-count":50,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2016,4,20]]}},"alternative-id":["10.1145\/2858657"],"URL":"https:\/\/doi.org\/10.1145\/2858657","relation":{},"ISSN":["1046-8188","1558-2868"],"issn-type":[{"type":"print","value":"1046-8188"},{"type":"electronic","value":"1558-2868"}],"subject":[],"published":{"date-parts":[[2016,2,8]]},"assertion":[{"value":"2015-04-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2015-11-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2016-02-08","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}