{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T15:09:50Z","timestamp":1767625790624,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819958467"},{"type":"electronic","value":"9789819958474"}],"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\/978-981-99-5847-4_14","type":"book-chapter","created":{"date-parts":[[2023,8,29]],"date-time":"2023-08-29T20:30:00Z","timestamp":1693341000000},"page":"191-201","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Hybrid Recommendation System with Graph Neural Collaborative Filtering and Local Self-attention Mechanism"],"prefix":"10.1007","author":[{"given":"Ao","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yifei","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shi","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhuo","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yifei","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiale","family":"Ju","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenya","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,8,30]]},"reference":[{"key":"14_CR1","doi-asserted-by":"crossref","unstructured":"Shang, M.-S.. Fu, Y., Chen, D.-B.: Personal recommendation using weighted bipartite graph projection. In: 2008 International Conference on Apperceiving Computing and Intelligence Analysis, pp. 198\u2013202 (2008)","DOI":"10.1109\/ICACIA.2008.4770004"},{"key":"14_CR2","doi-asserted-by":"crossref","unstructured":"Tong, L.: Personal recommendation based on community partition of bipartite network. In: 2015 International Conference on Cloud Computing and Big Data (CCBD), pp. 336\u2013341 (2015)","DOI":"10.1109\/CCBD.2015.44"},{"key":"14_CR3","doi-asserted-by":"crossref","unstructured":"Sun, J., Zhu, Z., Wang, Y.: Research on personalized recommendation case organization. In: 2010 International Conference on Innovative Computing and Communication and 2010 Asia-Pacific Conference on Information Technology and Ocean Engineering, pp. 312\u2013315 (2010)","DOI":"10.1109\/CICC-ITOE.2010.86"},{"key":"14_CR4","doi-asserted-by":"crossref","unstructured":"Yan, L.: Personalized recommendation method for e-commerce platform based on data mining technology. In: 2017 International Conference on Smart Grid and Electrical Automation (ICSGEA), pp. 514\u2013517 (2017)","DOI":"10.1109\/ICSGEA.2017.62"},{"key":"14_CR5","doi-asserted-by":"crossref","unstructured":"Li, X.: Research on the application of collaborative filtering algorithm in mobile e-commerce recommendation system. In: 2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC), pp. 924\u2013926 (2021)","DOI":"10.1109\/IPEC51340.2021.9421092"},{"key":"14_CR6","doi-asserted-by":"crossref","unstructured":"Xiaona, Z.: Personalized recommendation model for mobile e-commerce users. In: 2021 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), pp. 707\u2013710 (2021)","DOI":"10.1109\/ICMTMA52658.2021.00163"},{"key":"14_CR7","unstructured":"Chen, Y.-W., Xia, X., Shi, Y.-G.: A collaborative filtering recommendation algorithm based on contents\u2019 genome. In: IET International Conference on Information Science and Control Engineering 2012 (ICISCE 2012), pp. 1\u20134 (2012)"},{"key":"14_CR8","doi-asserted-by":"crossref","unstructured":"Shrivastava, N., Gupta, S.: Analysis on item-based and user-based collaborative filtering for movie recommendation system. In: 2021 5th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques (ICEECCOT), pp. 654\u2013656 (2021)","DOI":"10.1109\/ICEECCOT52851.2021.9707955"},{"key":"14_CR9","doi-asserted-by":"crossref","unstructured":"Embarak, O.H.: A method for solving the cold start problem in recommendation systems. In: 2011 International Conference on Innovations in Information Technology, pp. 238\u2013243 (2011)","DOI":"10.1109\/INNOVATIONS.2011.5893824"},{"key":"14_CR10","doi-asserted-by":"crossref","unstructured":"Gaspar, P., Kompan, M., Koncal, M., Bielikova, M.: Improving the personalized recommendation in the cold-start scenarios. In: 2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA), pp. 606\u2013607 (2019)","DOI":"10.1109\/DSAA.2019.00079"},{"key":"14_CR11","doi-asserted-by":"crossref","unstructured":"Paireekreng, W.: Mobile content recommendation system for re-visiting user using content-based filtering and client-side user profile. In: 2013 International Conference on Machine Learning and Cybernetics, pp. 1655\u20131660 (2013)","DOI":"10.1109\/ICMLC.2013.6890864"},{"key":"14_CR12","doi-asserted-by":"crossref","unstructured":"Pan, M., Yang, Y., Mi, Z.: Research on an extended SVD recommendation algorithm based on user\u2019s neighbor model. In: 2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS), pp. 81\u201384 (2016)","DOI":"10.1109\/ICSESS.2016.7883020"},{"key":"14_CR13","doi-asserted-by":"crossref","unstructured":"Shah, K., Salunke, A., Dongare, S., Antala, K.: Recommender systems: an overview of different approaches to recommendations. In: 2017 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), pp. 1\u20134 (2017)","DOI":"10.1109\/ICIIECS.2017.8276172"},{"key":"14_CR14","doi-asserted-by":"crossref","unstructured":"Huang, G.: E-commerce intelligent recommendation system based on deep learning. In: 2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC), pp. 1154\u20131157 (2022)","DOI":"10.1109\/IPEC54454.2022.9777500"},{"key":"14_CR15","doi-asserted-by":"crossref","unstructured":"Zarzour, H., Alsmirat, M., Jararweh, Y.: Using deep learning for positive reviews prediction in explainable recommendation systems. In: 2022 13th International Conference on Information and Communication Systems (ICICS), pp. 358\u2013362 (2022)","DOI":"10.1109\/ICICS55353.2022.9811151"},{"key":"14_CR16","doi-asserted-by":"crossref","unstructured":"Khanduri, S., Prabakeran, S.: Hybrid recommendation system with graph based and collaborative filtering recommendation systems. In: 2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon), pp. 1\u20137 (2022)","DOI":"10.1109\/MysuruCon55714.2022.9972677"},{"key":"14_CR17","doi-asserted-by":"crossref","unstructured":"Seng, D., Li, M., Zhang, X., Wang, J.: Research on neural graph collaborative filtering recommendation model fused with item temporal sequence relationships. IEEE Access 10, 116972\u2013116981 (2022)","DOI":"10.1109\/ACCESS.2022.3215161"},{"key":"14_CR18","doi-asserted-by":"crossref","unstructured":"Aljohani, A., Rakrouki, M.A., Alharbe, N., Alluhaibi, R.: A self-attention mask learning-based recommendation system. IEEE Access 10, pp. 93017\u201393028 (2022)","DOI":"10.1109\/ACCESS.2022.3202637"},{"key":"14_CR19","doi-asserted-by":"crossref","unstructured":"Keat, E.Y., et al.: Multiobjective deep reinforcement learning for recommendation systems. IEEE Access 10, 65011\u201365027 (2022)","DOI":"10.1109\/ACCESS.2022.3181164"},{"key":"14_CR20","doi-asserted-by":"crossref","unstructured":"Hou, Y.: Application of neural graph collaborative filtering in movie recommendation system. In: 2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI), pp. 113\u2013116 (2021)","DOI":"10.1109\/ICETCI53161.2021.9563481"},{"key":"14_CR21","doi-asserted-by":"crossref","unstructured":"Sangeetha, M., et al.: Predicting personalized recommendations using GNN. In: 2022 6th International Conference on Computing Methodologies and Communication (ICCMC), pp. 228\u2013234 (2022)","DOI":"10.1109\/ICCMC53470.2022.9753929"},{"key":"14_CR22","doi-asserted-by":"crossref","unstructured":"Liang, Z., Ding, H., Fu, W.: A survey on graph neural networks for recommendation. In: 2021 International Conference on Culture-oriented Science & Technology (ICCST), pp. 383\u2013386 (2021)","DOI":"10.1109\/ICCST53801.2021.00086"},{"key":"14_CR23","doi-asserted-by":"crossref","unstructured":"Zhao, J., Zhao, P., Zhao, L., Liu, Y., Sheng, V.S., Zhou, X.: Variational self-attention network for sequential recommendation. In: 2021 IEEE 37th International Conference on Data Engineering (ICDE), pp. 1559\u20131570 (2021)","DOI":"10.1109\/ICDE51399.2021.00138"},{"key":"14_CR24","doi-asserted-by":"crossref","unstructured":"Yin, Y., Huang, C., Sun, J., Huang, F.: Multi-head self-attention recommendation model based on feature interaction enhancement. In: ICC 2022 - IEEE International Conference on Communications, pp. 1740\u20131745 (2022)","DOI":"10.1109\/ICC45855.2022.9839284"},{"key":"14_CR25","doi-asserted-by":"crossref","unstructured":"Shi, X., Xu, M., Hu, J.: Long and short-term neural network news recommendation model based on self-attention mechanism. In: 2021 International Conference on Computer Information Science and Artificial Intelligence (CISAI), pp. 30\u201334 (2021)","DOI":"10.1109\/CISAI54367.2021.00014"}],"container-title":["Communications in Computer and Information Science","International Conference on Neural Computing for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-5847-4_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,27]],"date-time":"2024-10-27T02:09:05Z","timestamp":1729994945000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-5847-4_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819958467","9789819958474"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-5847-4_14","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"30 August 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NCAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Computing for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hefei","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"7 July 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 July 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ncaa2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/dl2link.com\/ncaa2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easy chair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"211","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"83","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"39% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.21","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.67","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}