{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T06:34:14Z","timestamp":1747809254937,"version":"3.37.3"},"reference-count":31,"publisher":"Wiley","license":[{"start":{"date-parts":[[2021,3,24]],"date-time":"2021-03-24T00:00:00Z","timestamp":1616544000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61672039","61602009","61772034","1908085MF190"],"award-info":[{"award-number":["61672039","61602009","61772034","1908085MF190"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003995","name":"Natural Science Foundation of Anhui Province","doi-asserted-by":"publisher","award":["61672039","61602009","61772034","1908085MF190"],"award-info":[{"award-number":["61672039","61602009","61772034","1908085MF190"]}],"id":[{"id":"10.13039\/501100003995","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Control Science and Engineering"],"published-print":{"date-parts":[[2021,3,24]]},"abstract":"<jats:p>In the cloud computing environment, there are huge amounts of functionally similar cloud services. Additionally, user requirements can change. Therefore, it is difficult to recommend services that meet users\u2019 requirements. To overcome the problems, a service recommendation method based on requirements is proposed. First, we form user communities by clustering to reduce the recommended range. Second, we use the reported QoS (Quality of Service) values and the evaluated QoS values to predict the QoS requirements of users. Third, based on the requirements, the matching degree of users to services is obtained. Finally, based on the similarity between the target user and the user\u2019s neighbors and the difference in their matching degree of service and the ratings of services by the neighbors, we can obtain a list of service recommendations for the target user. Compared to the traditional collaborative filtering method and the deviation-based method, our method improves the recommendation accuracy without lowering the efficiency.<\/jats:p>","DOI":"10.1155\/2021\/6669798","type":"journal-article","created":{"date-parts":[[2021,3,25]],"date-time":"2021-03-25T20:21:26Z","timestamp":1616703686000},"page":"1-11","source":"Crossref","is-referenced-by-count":4,"title":["A Service Recommendation Method Based on Requirements for the Cloud Environment"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3402-6391","authenticated-orcid":true,"given":"Liangmin","family":"Guo","sequence":"first","affiliation":[{"name":"School of Computer and Information, Anhui Normal University, Wuhu 241003, China"},{"name":"Anhui Provincial Key Laboratory of Network and Information Security, Wuhu 241003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaixuan","family":"Luan","sequence":"additional","affiliation":[{"name":"School of Computer and Information, Anhui Normal University, Wuhu 241003, China"},{"name":"Anhui Provincial Key Laboratory of Network and Information Security, Wuhu 241003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyao","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Computer and Information, Anhui Normal University, Wuhu 241003, China"},{"name":"Anhui Provincial Key Laboratory of Network and Information Security, Wuhu 241003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Qian","sequence":"additional","affiliation":[{"name":"School of Computer and Information, Anhui Normal University, Wuhu 241003, China"},{"name":"Anhui Provincial Key Laboratory of Network and Information Security, Wuhu 241003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1109\/SCC.2015.33"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.3969\/j.issn.0372-2112.2016.09.035"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1007\/s00530-017-0539-8"},{"key":"4","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1007\/978-3-540-72079-9_9","article-title":"Collaborative filtering recommender systems","volume":"4321","author":"J. 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