{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T07:46:22Z","timestamp":1743061582752,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":20,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811604782"},{"type":"electronic","value":"9789811604799"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-981-16-0479-9_7","type":"book-chapter","created":{"date-parts":[[2021,3,31]],"date-time":"2021-03-31T05:02:42Z","timestamp":1617166962000},"page":"83-95","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Learning Interests Oriented Model for Cold Start Recommendation"],"prefix":"10.1007","author":[{"given":"Yuefeng","family":"Du","sequence":"first","affiliation":[]},{"given":"Tuoyu","family":"Yan","sequence":"additional","affiliation":[]},{"given":"Xiaoli","family":"Li","sequence":"additional","affiliation":[]},{"given":"Jiafan","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Yang","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jing","family":"Shan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,4,1]]},"reference":[{"key":"7_CR1","unstructured":"Rocio, C., Pablo, C.: Should I follow the crowd? A probabilistic analysis of the effectiveness of popularity in recommender systems. In: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, Ann Arbor, pp. 415\u2013424. ACM (2018)"},{"key":"7_CR2","unstructured":"Liu, M.-J., Wang, W., Li, Y.: AttentionRank+: a graph recommendation algorithm based on attention relationship and multi-user behavior. Chin. J. Comput. 40, 102\u2013116 (2017)"},{"key":"7_CR3","doi-asserted-by":"crossref","unstructured":"Zhao, T., Mcauley, J., King, I.: Leveraging social connections to improve personalized ranking for collaborative filtering. In: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, Shanghai, pp. 261\u2013270. ACM (2014)","DOI":"10.1145\/2661829.2661998"},{"key":"7_CR4","doi-asserted-by":"crossref","unstructured":"Dao, T.H., Jeong, S.R., Ahn, H.: A novel recommendation model of location-based advertising: context-aware collaborative filtering using GA approach. Expert Syst. Appl. 39, 3731\u20133739 (2012)","DOI":"10.1016\/j.eswa.2011.09.070"},{"key":"7_CR5","unstructured":"Yu, Y., Qiu, G.: Friends recommendation algorithm for online social networks based on local random walks. Syst. Eng. 51\u201358 (2013)"},{"key":"7_CR6","doi-asserted-by":"crossref","unstructured":"Koren, Y.: Factorization meets the neighborhood: a multifaceted collaborative filtering model. In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Nevada, pp. 426\u2013434. ACM (2008)","DOI":"10.1145\/1401890.1401944"},{"key":"7_CR7","doi-asserted-by":"crossref","unstructured":"Wang, H., Wang, N., Yeung, D.Y.: Collaborative deep learning for recommender systems. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, pp. 261\u2013270. ACM (2015)","DOI":"10.1145\/2783258.2783273"},{"key":"7_CR8","doi-asserted-by":"publisher","first-page":"1090","DOI":"10.1109\/TMC.2013.133","volume":"13","author":"Y Komai","year":"2014","unstructured":"Komai, Y., Sasaki, Y., Hara, T., Nishio, S.: A KNN query processing method in mobile ad hoc networks. IEEE Trans. Mob. Comput. 13, 1090\u20131103 (2014)","journal-title":"IEEE Trans. Mob. Comput."},{"key":"7_CR9","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/S0898-1221(99)00144-3","volume":"37","author":"D Lu","year":"2017","unstructured":"Lu, D., Ning, M., Zang, J.: Improved KNN algorithm based on BP neural network decision. Comput. Appl. 37, 65\u201368 (2017)","journal-title":"Comput. Appl."},{"key":"7_CR10","unstructured":"Lu, Y., Hong, L.: A recommendation system algorithm based on real value and topology neural networks in social networks. J. San Ming Univ. 36\u201342 (2018)"},{"issue":"3","key":"7_CR11","doi-asserted-by":"publisher","first-page":"7401","DOI":"10.1007\/s10586-017-1576-y","volume":"22","author":"W Feng","year":"2018","unstructured":"Feng, W., Zhu, Q., Zhuang, J., Yu, S.: An expert recommendation algorithm based on Pearson correlation coefficient and FP-growth. Clust. Comput. 22(3), 7401\u20137412 (2018). https:\/\/doi.org\/10.1007\/s10586-017-1576-y","journal-title":"Clust. Comput."},{"key":"7_CR12","unstructured":"Chen, G., Wang, H.: Personalized recommendation algorithm based on improved Pearson correlation coefficient. J. Shandong Agric. Univ. (Nat. Sci. Edn.) 940\u2013944 (2016)"},{"key":"7_CR13","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/j.socnet.2005.01.007","volume":"27","author":"L Adamic","year":"2005","unstructured":"Adamic, L., Adar, E.: How to search a social network. Soc. Netw. 27, 187\u2013203 (2005)","journal-title":"Soc. Netw."},{"key":"7_CR14","doi-asserted-by":"crossref","unstructured":"Guy, I., Ronen, I., Wilcox, E.: Do you know? Recommending people to invite into your social network. In: Proceedings of the 14th International Conference on Intelligent User Interfaces, Florida, pp. 77\u201386. ACM (2009)","DOI":"10.1145\/1502650.1502664"},{"key":"7_CR15","doi-asserted-by":"publisher","first-page":"1019","DOI":"10.1002\/asi.20591","volume":"58","author":"D Liben-Nowell","year":"2007","unstructured":"Liben-Nowell, D., Kleinberg, J.: The link-prediction problem for social networks. J. Am. Soc. Inf. Sci. Technol. 58, 1019\u20131031 (2007)","journal-title":"J. Am. Soc. Inf. Sci. Technol."},{"key":"7_CR16","unstructured":"Cheng, L., Gao, M.: Recommendation algorithm based on deep neural network. Mod. Comput. (Prof. Ed.) 5\u20139 (2018)"},{"key":"7_CR17","doi-asserted-by":"publisher","first-page":"1331","DOI":"10.1093\/comjnl\/bxt086","volume":"57","author":"J Sun","year":"2014","unstructured":"Sun, J., Ma, J., Liu, Z.: Leveraging content and connections for scientific article recommendation in social computing contexts. Comput. J. 57, 1331\u20131342 (2014)","journal-title":"Comput. J."},{"key":"7_CR18","doi-asserted-by":"crossref","unstructured":"Ma, H., Yang, H., Lyu, M.R.: SoRec: social recommendation using probabilistic matrix factorization. In: Proceedings of the 17th ACM Conference on Information and Knowledge Management, pp. 931\u2013940. ACM (2008)","DOI":"10.1145\/1458082.1458205"},{"key":"7_CR19","doi-asserted-by":"crossref","unstructured":"Zhao, H., Yao, Q., Li, J.: Meta-graph based recommendation fusion over heterogeneous information networks. In: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, pp. 635\u2013644. ACM (2017)","DOI":"10.1145\/3097983.3098063"},{"key":"7_CR20","doi-asserted-by":"crossref","unstructured":"Shen, Y., Jin, R.: Learning personal + social latent factor model for social recommendation. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Beijing, pp. 1303\u20131311. ACM (2012)","DOI":"10.1145\/2339530.2339732"}],"container-title":["Communications in Computer and Information Science","Web and Big Data. APWeb-WAIM 2020 International Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-0479-9_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,25]],"date-time":"2021-04-25T00:19:58Z","timestamp":1619309998000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-0479-9_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9789811604782","9789811604799"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-0479-9_7","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"1 April 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"APWeb-WAIM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tianjin","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":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 August 2020","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":"apwebwaim2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.tjudb.cn\/apwebwaim2020\/","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":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"259","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":"68","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":"37","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":"26% - 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","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":"4.6","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)"}},{"value":"Due to the COVID-19 pandemic the conference was organized as a fully online conference.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}