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Thus, the paper puts forward a new service composition recommendation method. The method is composed of two steps: the first step is service component recommendation based on recurrent neural network (RNN). When a user selects a service component, the RNN algorithm is exploited to recommend other matched services to the user, aiding the completion of a service composition. The second step is service composition recommendation based on Naive Bayes. When the user completes a service composition, considering the diversity of user interests, the Bayesian classifier is used to model their interests, and other service compositions that satisfy the user interests are recommended to the user. Experiments show that the proposed method can accurately recommend relevant service components and service compositions to users.<\/jats:p>","DOI":"10.1155\/2021\/1013682","type":"journal-article","created":{"date-parts":[[2021,10,29]],"date-time":"2021-10-29T21:20:09Z","timestamp":1635542409000},"page":"1-9","source":"Crossref","is-referenced-by-count":5,"title":["Service Composition Recommendation Method Based on Recurrent Neural Network and Naive Bayes"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4029-2621","authenticated-orcid":true,"given":"Ming","family":"Chen","sequence":"first","affiliation":[{"name":"College of Software Engineering, Zhengzhou University of Light Industry, Zhengzhou 450000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8852-0160","authenticated-orcid":true,"given":"Junqiang","family":"Cheng","sequence":"additional","affiliation":[{"name":"Europe-Asia Hi-tech and Digital Technology Company Limited, Zhengzhou 450000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4596-6565","authenticated-orcid":true,"given":"Guanghua","family":"Ma","sequence":"additional","affiliation":[{"name":"Key Laboratory of Data Analysis and Financial Risk Prediction, Xinxiang University, Xinxiang 458000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9625-8326","authenticated-orcid":true,"given":"Liang","family":"Tian","sequence":"additional","affiliation":[{"name":"Institute of Computer and Information Engineering, Xinxiang University, Xinxiang 458000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1113-1527","authenticated-orcid":true,"given":"Xiaohong","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Data Analysis and Financial Risk Prediction, Xinxiang University, Xinxiang 458000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2554-5106","authenticated-orcid":true,"given":"Qingmin","family":"Shi","sequence":"additional","affiliation":[{"name":"Key Laboratory of Data Analysis and Financial Risk Prediction, Xinxiang University, Xinxiang 458000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1002\/bltj.20363"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1109\/iV.2018.00088"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-59480-4_49"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1145\/1558334.1558343"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-45005-1_12"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1109\/ICWS.2015.38"},{"first-page":"995","article-title":"Factorization machines","author":"S. 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