{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T13:29:21Z","timestamp":1762867761219,"version":"build-2065373602"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030161835"},{"type":"electronic","value":"9783030161842"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-16184-2_46","type":"book-chapter","created":{"date-parts":[[2019,3,29]],"date-time":"2019-03-29T13:04:26Z","timestamp":1553864666000},"page":"483-491","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Features Weight Estimation Using a Genetic Algorithm for Customer Churn Prediction in the Telecom Sector"],"prefix":"10.1007","author":[{"given":"Adnan","family":"Amin","sequence":"first","affiliation":[]},{"given":"Babar","family":"Shah","sequence":"additional","affiliation":[]},{"given":"Ali","family":"Abbas","sequence":"additional","affiliation":[]},{"given":"Sajid","family":"Anwar","sequence":"additional","affiliation":[]},{"given":"Omar","family":"Alfandi","sequence":"additional","affiliation":[]},{"given":"Fernando","family":"Moreira","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,3,30]]},"reference":[{"key":"46_CR1","doi-asserted-by":"crossref","unstructured":"Sharma, N., Saroha, K.: Study of dimension reduction methodologies in data mining. In: International Conference on Computing, Communication & Automation, pp. 133\u2013137 (2015)","DOI":"10.1109\/CCAA.2015.7148359"},{"key":"46_CR2","first-page":"1","volume":"2015","author":"Xin-She Yang","year":"2015","unstructured":"Yang, X.-S., Lee, S., Lee, S., Theera-Umpon, N.: Information analysis of high-dimensional data and applications. Math. Probl. Eng. 1\u20136 (2015)","journal-title":"Mathematical Problems in Engineering"},{"key":"46_CR3","doi-asserted-by":"crossref","unstructured":"Amin, A., Rahim, F., Ramzan, M., Anwar, S.: Prudent based approach for customer churn prediction (2015)","DOI":"10.1007\/978-3-319-18422-7_29"},{"key":"46_CR4","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1016\/j.eswa.2016.07.041","volume":"64","author":"R Houaria","year":"2016","unstructured":"Houaria, R., Bounceur, A., Kechadic, T., Taria, A.-K., Euler, R.: Dimensionality reduction in data mining: a Copula approach. Expert Syst. Appl. 64, 247\u2013260 (2016)","journal-title":"Expert Syst. Appl."},{"key":"46_CR5","first-page":"1","volume":"9","author":"K Fodor Imola","year":"2009","unstructured":"Fodor Imola, K.: A survey of dimension reduction techniques. Cent. Appl. Sci. Comput. Lawrence Livermore Natl. Lab. 9, 1\u201318 (2009)","journal-title":"Cent. Appl. Sci. Comput. Lawrence Livermore Natl. Lab."},{"key":"46_CR6","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1016\/j.jbusres.2017.12.047","volume":"94","author":"J Martins","year":"2019","unstructured":"Martins, J., Costa, C., Oliveira, T., Gon\u00e7alves, R., Branco, F.: How smartphone advertising influences consumers\u2019 purchase intention. J. Bus. Res. 94, 378\u2013387 (2019)","journal-title":"J. Bus. Res."},{"key":"46_CR7","first-page":"1","volume":"2015","author":"L Hongjiu","year":"2015","unstructured":"Hongjiu, L., Yanrong, H.: An evaluating method with combined assigning-weight based on maximizing variance. Sci. Program. 2015, 1\u20138 (2015)","journal-title":"Sci. Program."},{"key":"46_CR8","unstructured":"Frank, E., Hall, M., Pfahringer, B.: Locally weighted Naive Bayes. In: Proceedings of the 19th Conference on Uncertainty in Artificial Intelligence, pp. 249\u2013256 (2003)"},{"key":"46_CR9","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1080\/17517575.2013.860481","volume":"8","author":"L Wang","year":"2014","unstructured":"Wang, L., Ji, P., Qi, J., Shan, S., Bi, Z., Deng, W., Zhang, N.: Feature weighted na\u00efve Bayes algorithm for information retrieval of enterprise systems. Enterp. Inf. Syst. 8, 107\u2013120 (2014)","journal-title":"Enterp. Inf. Syst."},{"key":"46_CR10","doi-asserted-by":"publisher","first-page":"839","DOI":"10.1007\/s00607-018-0633-6","volume":"100","author":"J Vijaya","year":"2018","unstructured":"Vijaya, J., Sivasankar, E.: Computing efficient features using rough set theory combined with ensemble classification techniques to improve the customer churn prediction in telecommunication sector. Computing 100, 839\u2013860 (2018)","journal-title":"Computing"},{"key":"46_CR11","doi-asserted-by":"publisher","first-page":"320","DOI":"10.1007\/978-3-319-18422-7_29","volume-title":"Beyond Databases, Architectures and Structures","author":"Adnan Amin","year":"2015","unstructured":"Amin, A., Faisal, R., Muhammad, R., Sajid, A.: A prudent based approach for customer churn prediction. In: 11th International Conference, BDAS 2015, Ustro\u0144, Poland, pp. 320\u2013332 (2015)"},{"key":"46_CR12","doi-asserted-by":"crossref","unstructured":"Adnan, A., Babar, S., Asad Masood, K., Thar, B., Hamood ur Rahman, D., Sajid, A.: Just-in-time customer churn prediction: with and without data transformation. In: IEEE CEC 2018, Rio de Janeiro, Brazil, pp. 1\u20137 (2018)","DOI":"10.1109\/CEC.2018.8477954"},{"key":"46_CR13","doi-asserted-by":"publisher","first-page":"7940","DOI":"10.1109\/ACCESS.2016.2619719","volume":"4","author":"A Amin","year":"2016","unstructured":"Amin, A., Anwar, S., Adnan, A., Nawaz, M.: Comparing oversampling techniques to handle the class imbalance problem: a customer churn prediction case study. J. IEEE Access 4, 7940\u20137957 (2016)","journal-title":"J. IEEE Access"},{"key":"46_CR14","doi-asserted-by":"crossref","unstructured":"Zhang, H., Shengli, S.: Learning weighted Naive Bayes with accurate ranking. In: Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM 2004), pp. 4\u20137 (2004)","DOI":"10.1109\/ICDM.2004.10030"},{"key":"46_CR15","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1007\/978-1-84628-663-6_5","volume-title":"Research and Development in Intelligent Systems XXIII","author":"Mark Hall","year":"2007","unstructured":"Hall, M.: A decision tree-based attribute weighting filter for Naive Bayes. In: Research and Development in Intelligent Systems XXIII - Proceedings of AI 2006, the 26th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, pp. 59\u201370 (2007)"},{"key":"46_CR16","first-page":"1672","volume":"5","author":"J Wu","year":"2011","unstructured":"Wu, J., Cai, Z.: Attribute weighting via differential evolution algorithm for attribute Weighted Naive Bayes (WNB). J. Comput. Inf. Syst. 5, 1672\u20131679 (2011)","journal-title":"J. Comput. Inf. Syst."},{"key":"46_CR17","first-page":"1947","volume":"14","author":"NA Zaidi","year":"2013","unstructured":"Zaidi, N.A., Cerquides, J., Carman, M.J., Webb, G.I.: Alleviating naive Bayes attribute independence assumption by attribute weighting. Mach. Learn. Res. 14, 1947\u20131988 (2013)","journal-title":"Mach. Learn. Res."},{"key":"46_CR18","doi-asserted-by":"publisher","first-page":"6575","DOI":"10.1016\/j.eswa.2014.05.014","volume":"41","author":"K Kim","year":"2014","unstructured":"Kim, K., Jun, C.-H., Lee, J.: Improved churn prediction in telecommunication industry by analyzing a large network. Expert Syst. Appl. 41, 6575\u20136584 (2014)","journal-title":"Expert Syst. Appl."},{"key":"46_CR19","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.engappai.2016.02.002","volume":"52","author":"L Jiang","year":"2016","unstructured":"Jiang, L., Li, C., Wang, S., Zhang, L.: Deep feature weighting for naive Bayes and its application to text classification. Eng. Appl. Artif. Intell. 52, 26\u201339 (2016)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"46_CR20","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/j.knosys.2016.02.017","volume":"100","author":"L Zhang","year":"2016","unstructured":"Zhang, L., Jiang, L., Li, C., Kong, G.: Two feature weighting approaches for naive Bayes text classifiers. Knowl.-Based Syst. 100, 137\u2013144 (2016)","journal-title":"Knowl.-Based Syst."},{"key":"46_CR21","doi-asserted-by":"crossref","unstructured":"Amin, A., Shah, B., Khattak, A.M., Baker, T., Durani, Hamood ur Rahman, D., Anwar, S.: Just-in-time customer churn prediction: with and without data transformation. J. Bus. Res. 1\u20135 (2018)","DOI":"10.1109\/CEC.2018.8477954"},{"key":"46_CR22","first-page":"1","volume":"4","author":"A Amin","year":"2016","unstructured":"Amin, A., Anwar, S., Adnan, A., Nawaz, M., Alawfi, K., Huang, K., Hussain, A.: Customer churn prediction in telecommunication sector using rough set approach. Neurocomputing 4, 1\u201318 (2016)","journal-title":"Neurocomputing"},{"key":"46_CR23","doi-asserted-by":"publisher","first-page":"434","DOI":"10.1109\/TR.2013.2259203","volume":"62","author":"W Shuo","year":"2013","unstructured":"Shuo, W., Xin, Y.: Using class imbalance learning for software defect prediction. IEEE Trans. Reliab. 62, 434\u2013443 (2013)","journal-title":"IEEE Trans. Reliab."},{"key":"46_CR24","volume-title":"Data Mining: Concepts and Techniques","author":"J Han","year":"2011","unstructured":"Han, J., Kamber, M., Pei, J.: Data Mining: Concepts and Techniques, 3rd edn. Morgan Kaufmann, Burlington (2011)","edition":"3"}],"container-title":["Advances in Intelligent Systems and Computing","New Knowledge in Information Systems and Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-16184-2_46","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T04:12:49Z","timestamp":1761279169000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-16184-2_46"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030161835","9783030161842"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-16184-2_46","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"30 March 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WorldCIST'19","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"World Conference on Information Systems and Technologies","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Galicia","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 April 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 April 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"worldcist2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.worldcist.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}