{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T11:58:39Z","timestamp":1743076719682,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":13,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819967018"},{"type":"electronic","value":"9789819967025"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-981-99-6702-5_46","type":"book-chapter","created":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T18:02:42Z","timestamp":1700503362000},"page":"565-575","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Novel LRKS-WSQoS Model for Web Service Quality Estimation Using Machine Learning-Based Linear Regression and Kappa Methods"],"prefix":"10.1007","author":[{"given":"K.","family":"Prakash","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Kalaiarasan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,11,21]]},"reference":[{"key":"46_CR1","doi-asserted-by":"crossref","unstructured":"Apte, V., Viswanath, T., Gawali, D., Kommireddy, A., Gupta, A.: AutoPerf: automated load testing and resource usage profiling of multitier internet applications. In: Proceedings of the 8th ACM\/SPEC on International Conference on Performance Engineering, pp. 115\u2013126. ACM (2017)","DOI":"10.1145\/3030207.3030222"},{"key":"46_CR2","first-page":"92","volume-title":"Adaptive Service Composition Based on Reinforcement Learning","author":"H Wang","year":"2010","unstructured":"Wang, H., Zhou, X., Zhou, X., Liu, W., Li, W., Bouguettaya, A.: Adaptive Service Composition Based on Reinforcement Learning, pp. 92\u2013107. Springer, Berlin, Germany (2010)"},{"key":"46_CR3","doi-asserted-by":"crossref","unstructured":"Rhmann, W., Pandey, B., Ansari, G., Pandey, D.K.: Software fault prediction based on change metrics using hybrid algorithms: an empirical study. J. King Saud Univ. Comput. Inf. Sci. 32(4), 419\u2013424 (2020)","DOI":"10.1016\/j.jksuci.2019.03.006"},{"key":"46_CR4","unstructured":"Ren, L., Wang, W., Xu, H.: A reinforcement learning method for constraint-satisfied services composition. IEEE Transactions on Services Computing, vol. 1. IEEE Computer Society, Los Alamitos, CA, USA (2017)"},{"key":"46_CR5","unstructured":"Mostafa, A., Zhang, M.: Multi-objective service composition in uncertain environments. IEEE Trans. Serv. Comput. (2015)"},{"key":"46_CR6","doi-asserted-by":"crossref","unstructured":"Hasnain, M., Pasha, M.F., Ghani, I., Mehboob, B., Imran, M., Ali, A.: Benchmark dataset selection of web services technologies: a factor analysis. IEEE Access 8, 53649\u201353665 (2020)","DOI":"10.1109\/ACCESS.2020.2979253"},{"key":"46_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2019.09.009","volume":"102","author":"F Lopes","year":"2020","unstructured":"Lopes, F., Agnelo, J., Teixeira, C.A., Laranjeiro, N., Bernardino, J.: Automating orthogonal defect classication using machine learning algorithms. Future Gener. Comput. Syst. 102, 932947 (2020)","journal-title":"Future Gener. Comput. Syst."},{"key":"46_CR8","doi-asserted-by":"crossref","unstructured":"Singh, D., Singh, B.: Investigating the impact of data normalization on classification performance. Appl. Soft Comput. 105524 (2019)","DOI":"10.1016\/j.asoc.2019.105524"},{"key":"46_CR9","doi-asserted-by":"crossref","unstructured":"Ben-David, A., Frank, E.: Accuracy of machine learning models versus \u2018hand crafted\u2019 expert systems\u2014a credit scoring case study. Expert Syst. Appl. 36(3), 5264\u20135271 (2009)","DOI":"10.1016\/j.eswa.2008.06.071"},{"key":"46_CR10","doi-asserted-by":"crossref","unstructured":"Dantas, J., Matos, R., Araujo, J., Oliveira, D., Oliveira, A., Maciel, P.: Hierarchical model and sensitivity analysis for a cloud-based VoD streaming service. In: Proceedings of the 46th Annual IEEE\/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W), Jun 2016, pp. 10\u201316","DOI":"10.1109\/DSN-W.2016.23"},{"key":"46_CR11","doi-asserted-by":"crossref","unstructured":"Ibrahim, A.A.Z.A.: PRESENCE: a framework for monitoring, modelling and evaluating the performance of cloud SaaS web services. In: Proceedings of the 48th Annual IEEE\/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W), Jun 2018, pp. 83\u201386","DOI":"10.1109\/DSN-W.2018.00041"},{"key":"46_CR12","doi-asserted-by":"crossref","unstructured":"Li, L., Liu, M., Shen, W., Cheng, G.: Recommending mobile services with trustworthy QoS and dynamic user preferences via FAHP and ordinal utility function. IEEE Trans. Mob. Comput. 19(2), 419\u2013431 (2020)","DOI":"10.1109\/TMC.2019.2896239"},{"key":"46_CR13","doi-asserted-by":"crossref","unstructured":"Ouadah, A., Hadjali, A., Nader, F., Benouaret, K.: SEFAP: an efficient approach for ranking skyline web services. J. Ambient Intell. Human. Comput. 10(2), 709\u2013725 (2019)","DOI":"10.1007\/s12652-018-0721-7"}],"container-title":["Smart Innovation, Systems and Technologies","Evolution in Computational Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-6702-5_46","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,9]],"date-time":"2024-10-09T06:12:02Z","timestamp":1728454322000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-6702-5_46"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819967018","9789819967025"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-6702-5_46","relation":{},"ISSN":["2190-3018","2190-3026"],"issn-type":[{"type":"print","value":"2190-3018"},{"type":"electronic","value":"2190-3026"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"21 November 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"FICTA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Frontiers of Intelligent Computing: Theory and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cardiff","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 April 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 April 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ficta2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ficta.co.uk\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}