A method to recommend cloud manufacturing service based on the spectral clustering and improved Slope one algorithm
Abstract The booming growth of cloud manufacturing services provides users with more choices. However, cloud manufacturing service recommendation remains a challenging issue due to numerous similar candidate services and diverse user preferences. The purpose of this paper is to provide an efficient...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2023-08-01
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| Series: | Journal of Cloud Computing: Advances, Systems and Applications |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13677-023-00489-5 |
| _version_ | 1797451495759675392 |
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| author | Qiang Hu Haoquan Qi Wen Huang Minghua Liu |
| author_facet | Qiang Hu Haoquan Qi Wen Huang Minghua Liu |
| author_sort | Qiang Hu |
| collection | DOAJ |
| description | Abstract The booming growth of cloud manufacturing services provides users with more choices. However, cloud manufacturing service recommendation remains a challenging issue due to numerous similar candidate services and diverse user preferences. The purpose of this paper is to provide an efficient and accurate cloud manufacturing service recommendation method. A spectral clustering algorithm is first designed to cluster the cloud manufacturing services. Then the candidate rating service set is constructed based on the service clusters by service function comparison and parameter matching. Finally, an improved Slope one algorithm, which integrates user similarity and service similarity, is proposed to rate the cloud manufacturing services. The top-k services with the highest scores are recommended to the users. Experiments show that the proposed method can provide more accurate service rating with less time consumption. The service recommendation performance of this method is also proved to be superior to other methods in terms of precision, recall, and F-score. |
| first_indexed | 2024-03-09T14:55:29Z |
| format | Article |
| id | doaj.art-b0068e944e1f435da869662a646dc9e6 |
| institution | Directory Open Access Journal |
| issn | 2192-113X |
| language | English |
| last_indexed | 2024-03-09T14:55:29Z |
| publishDate | 2023-08-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Cloud Computing: Advances, Systems and Applications |
| spelling | doaj.art-b0068e944e1f435da869662a646dc9e62023-11-26T14:14:54ZengSpringerOpenJournal of Cloud Computing: Advances, Systems and Applications2192-113X2023-08-0112111710.1186/s13677-023-00489-5A method to recommend cloud manufacturing service based on the spectral clustering and improved Slope one algorithmQiang Hu0Haoquan Qi1Wen Huang2Minghua Liu3College of Information Science and Technology, Qingdao University of Science and TechnologyCollege of Information Science and Technology, Qingdao University of Science and TechnologyCollege of Information Science and Technology, Qingdao University of Science and TechnologyCollege of Information Science and Technology, Qingdao University of Science and TechnologyAbstract The booming growth of cloud manufacturing services provides users with more choices. However, cloud manufacturing service recommendation remains a challenging issue due to numerous similar candidate services and diverse user preferences. The purpose of this paper is to provide an efficient and accurate cloud manufacturing service recommendation method. A spectral clustering algorithm is first designed to cluster the cloud manufacturing services. Then the candidate rating service set is constructed based on the service clusters by service function comparison and parameter matching. Finally, an improved Slope one algorithm, which integrates user similarity and service similarity, is proposed to rate the cloud manufacturing services. The top-k services with the highest scores are recommended to the users. Experiments show that the proposed method can provide more accurate service rating with less time consumption. The service recommendation performance of this method is also proved to be superior to other methods in terms of precision, recall, and F-score.https://doi.org/10.1186/s13677-023-00489-5Cloud manufacturing serviceService similarityService ratingSlope one |
| spellingShingle | Qiang Hu Haoquan Qi Wen Huang Minghua Liu A method to recommend cloud manufacturing service based on the spectral clustering and improved Slope one algorithm Journal of Cloud Computing: Advances, Systems and Applications Cloud manufacturing service Service similarity Service rating Slope one |
| title | A method to recommend cloud manufacturing service based on the spectral clustering and improved Slope one algorithm |
| title_full | A method to recommend cloud manufacturing service based on the spectral clustering and improved Slope one algorithm |
| title_fullStr | A method to recommend cloud manufacturing service based on the spectral clustering and improved Slope one algorithm |
| title_full_unstemmed | A method to recommend cloud manufacturing service based on the spectral clustering and improved Slope one algorithm |
| title_short | A method to recommend cloud manufacturing service based on the spectral clustering and improved Slope one algorithm |
| title_sort | method to recommend cloud manufacturing service based on the spectral clustering and improved slope one algorithm |
| topic | Cloud manufacturing service Service similarity Service rating Slope one |
| url | https://doi.org/10.1186/s13677-023-00489-5 |
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