{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T06:19:50Z","timestamp":1770617990795,"version":"3.49.0"},"reference-count":28,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,1,30]],"date-time":"2021-01-30T00:00:00Z","timestamp":1611964800000},"content-version":"vor","delay-in-days":29,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003397","name":"Huazhong University of Science and Technology","doi-asserted-by":"publisher","award":["450\/5003450017"],"award-info":[{"award-number":["450\/5003450017"]}],"id":[{"id":"10.13039\/501100003397","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["300102240105"],"award-info":[{"award-number":["300102240105"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>This paper considers current personalized recommendation approaches based on computational social systems and then discusses their advantages and application environments. The most widely used recommendation algorithm, personalized advice based on collaborative filtering, is selected as the primary research focus. Some improvements in its application performance are analyzed. First, for the calculation of user similarity, the introduction of computational social system attributes can help to determine users\u2019 neighbors more accurately. Second, computational social system strategies can be adopted to penalize popular items. Third, the network community, identity, and trust can be combined as there is a close relationship. Therefore, this paper proposes a new method that uses a computational social system, including a trust model based on community relationships, to improve the user similarity calculation accuracy to enhance personalized recommendation. Finally, the improved algorithm in this paper is tested on the online reading website dataset. The experimental results show that the enhanced collaborative filtering algorithm performs better than the traditional algorithm.<\/jats:p>","DOI":"10.1155\/2021\/6651493","type":"journal-article","created":{"date-parts":[[2021,1,30]],"date-time":"2021-01-30T23:35:07Z","timestamp":1612049707000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Communication\u2010Based Book Recommendation in Computational Social Systems"],"prefix":"10.1155","volume":"2021","author":[{"given":"Long","family":"Zuo","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0531-9179","authenticated-orcid":false,"given":"Shuo","family":"Xiong","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Qi","sequence":"additional","affiliation":[]},{"given":"Zheng","family":"Wen","sequence":"additional","affiliation":[]},{"given":"Yiwen","family":"Tang","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,1,30]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.procir.2019.04.126"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00779-018-01194-w"},{"key":"e_1_2_9_3_2","first-page":"1","article-title":"Vehicle trajectory clustering based on dynamic representation learning of internet of vehicles","author":"Wang W.","year":"2020","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"e_1_2_9_4_2","first-page":"1","article-title":"An attention-based deep learning framework for trip destination prediction of sharing bike","author":"Wang W.","year":"2020","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"e_1_2_9_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/138859.138867"},{"key":"e_1_2_9_6_2","unstructured":"BreeseJ. S. HeckermanD. andKadieC. Empirical analysis of predictive algorithms for collaborative filtering 2013 https:\/\/arxiv.org\/ftp\/arxiv\/papers\/1301\/1301.7363.pdf."},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/mnet.011.2000250"},{"key":"e_1_2_9_8_2","article-title":"Collaborative filtering with network representation learning for citation recommendation","author":"Wang W.","year":"2020","journal-title":"IEEE Transactions on Big Data"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781316257340"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.joi.2020.101041"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.3233\/jifs-169973"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.2478\/cait-2019-0006"},{"key":"e_1_2_9_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.simpat.2020.102215"},{"key":"e_1_2_9_14_2","article-title":"Robust spammer detection using collaborative neural network in internet of thing applications","author":"Guo Z.","year":"2020","journal-title":"IEEE Internet of Things Journal"},{"key":"e_1_2_9_15_2","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/1716352"},{"key":"e_1_2_9_16_2","doi-asserted-by":"crossref","unstructured":"SarwarB. GeorgeK. JosephK. andRiedlJ. Item-based collaborative filtering recommendation algorithms Proceedings of the 10th International Conference on World Wide Web April 2001 Hong Kong China 285\u2013295.","DOI":"10.1145\/371920.372071"},{"key":"e_1_2_9_17_2","doi-asserted-by":"crossref","unstructured":"GetoorL.andSahamiM. Using probabilistic relational models for collaborative filtering Proceedings of the workshop on web usage analysis and user profiling (WEBKDD\u201999) August 1999 San Diego CA USA 1\u20136.","DOI":"10.1145\/846183.846209"},{"key":"e_1_2_9_18_2","doi-asserted-by":"publisher","DOI":"10.1145\/963770.963776"},{"key":"e_1_2_9_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2004.1264822"},{"key":"e_1_2_9_20_2","unstructured":"LyleH.andFosterD. P. Clustering methods for collaborative filtering Proceedings of the AAAI workshop on recommendation systems 1998 Menlo Park CA USA 114\u2013129."},{"key":"e_1_2_9_21_2","doi-asserted-by":"publisher","DOI":"10.1142\/s021800140700548x"},{"key":"e_1_2_9_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2007.02.008"},{"key":"e_1_2_9_23_2","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/1716352"},{"key":"e_1_2_9_24_2","doi-asserted-by":"publisher","DOI":"10.1080\/01449290110084683"},{"key":"e_1_2_9_25_2","first-page":"50","article-title":"The co-creation connection","author":"Coimbatore K. P.","year":"2002","journal-title":"Strategy and Business"},{"key":"e_1_2_9_26_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2006.11.003"},{"key":"e_1_2_9_27_2","doi-asserted-by":"crossref","unstructured":"DavidsonJ. LiebaldB. LiuJ.et al. The youtube video recommendation system Proceedings of the Fourth ACM Conference on Recommender Systems September 2010 New York NY USA 293\u2013296.","DOI":"10.1145\/1864708.1864770"},{"key":"e_1_2_9_28_2","doi-asserted-by":"crossref","unstructured":"CuiP. WangZ. andZhouSu What videos are similar with you? learning a common attributed representation for video recommendation Proceedings of the 22nd ACM International Conference on Multimedia October 2014 Orlando FL USA 597\u2013606.","DOI":"10.1145\/2647868.2654946"}],"container-title":["Complexity"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2021\/6651493.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2021\/6651493.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/2021\/6651493","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,9]],"date-time":"2024-08-09T22:42:18Z","timestamp":1723243338000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/2021\/6651493"}},"subtitle":[],"editor":[{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":28,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["10.1155\/2021\/6651493"],"URL":"https:\/\/doi.org\/10.1155\/2021\/6651493","archive":["Portico"],"relation":{},"ISSN":["1076-2787","1099-0526"],"issn-type":[{"value":"1076-2787","type":"print"},{"value":"1099-0526","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"2020-12-04","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-01-11","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-01-30","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"6651493"}}