{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,4]],"date-time":"2026-01-04T14:53:23Z","timestamp":1767538403592},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030295158"},{"type":"electronic","value":"9783030295165"}],"license":[{"start":{"date-parts":[[2019,8,24]],"date-time":"2019-08-24T00:00:00Z","timestamp":1566604800000},"content-version":"tdm","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":[[2020]]},"DOI":"10.1007\/978-3-030-29516-5_3","type":"book-chapter","created":{"date-parts":[[2019,8,23]],"date-time":"2019-08-23T16:03:48Z","timestamp":1566576228000},"page":"18-28","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Switching Approach that Improves Prediction Accuracy for Long Tail Recommendations"],"prefix":"10.1007","author":[{"given":"Gharbi","family":"Alshammari","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jose L.","family":"Jorro-Aragoneses","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stelios","family":"Kapetanakis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nikolaos","family":"Polatidis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miltos","family":"Petridis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,8,24]]},"reference":[{"key":"3_CR1","unstructured":"Abdollahpouri, H., Burke, R., Mobasher, B.: Value-aware item weighting for long-tail recommendation. arXiv preprint (2018). arXiv:1802.05382"},{"key":"3_CR2","doi-asserted-by":"crossref","unstructured":"Alshammari, G., Jorro-Aragoneses, J.L., Kapetanakis, S., Petridis, M., Recio-Garc\u00eda, J.A., D\u00edaz-Agudo, B.: A hybrid cbr approach for the long tail problem in recommender systems. In: International Conference on Case-Based Reasoning, pp. 35\u201345. Springer (2017)","DOI":"10.1007\/978-3-319-61030-6_3"},{"key":"3_CR3","doi-asserted-by":"crossref","unstructured":"Alshammari, G., Kapetanakis, S., Polatidis, N., Petridis, M.: A triangle multi-level item-based collaborative filtering method that improves recommendations. In: International Conference on Engineering Applications of Neural Networks, pp. 145\u2013157. Springer (2018)","DOI":"10.1007\/978-3-319-98204-5_12"},{"issue":"3","key":"3_CR4","first-page":"1","volume":"24","author":"C Anderson","year":"2007","unstructured":"Anderson, C.: The long tail: why the future of business is selling less of more by Chris Anderson. J. Prod. Innovation Manag. 24(3), 1\u201330 (2007)","journal-title":"J. Prod. Innovation Manag."},{"key":"3_CR5","doi-asserted-by":"crossref","unstructured":"Ayub, M., Ghazanfar, M.A., Maqsood, M., Saleem, A.: A jaccard base similarity measure to improve performance of cf based recommender systems. In: 2018 International Conference on Information Networking (ICOIN), pp. 1\u20136. IEEE (2018)","DOI":"10.1109\/ICOIN.2018.8343073"},{"key":"3_CR6","unstructured":"Breese, J.S., Heckerman, D., Kadie, C.: Empirical analysis of predictive algorithms for collaborative filtering. In: Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence, pp. 43\u201352. Morgan Kaufmann Publishers Inc. (1998)"},{"issue":"4","key":"3_CR7","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1023\/A:1021240730564","volume":"12","author":"R Burke","year":"2002","unstructured":"Burke, R.: Hybrid recommender systems: survey and experiments. User Model. User-Adap. Inter. 12(4), 331\u2013370 (2002)","journal-title":"User Model. User-Adap. Inter."},{"key":"3_CR8","first-page":"73","volume":"9343","author":"S Craw","year":"2015","unstructured":"Craw, S., Horsburgh, B., Massie, S.: Music recommendation: audio neighbourhoods to discover music in the long tail. Lect. Notes Comput. Sci. (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 9343, 73\u201387 (2015)","journal-title":"Lect. Notes Comput. Sci. (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)"},{"key":"3_CR9","doi-asserted-by":"crossref","unstructured":"Cremonesi, P., Koren, Y., Turrin, R.: Performance of recommender algorithms on top-n recommendation tasks. In: Proceedings of the Fourth ACM Conference on Recommender Systems - RecSys 2010 p. 39 (2010)","DOI":"10.1145\/1864708.1864721"},{"key":"3_CR10","doi-asserted-by":"crossref","unstructured":"Gedikli, F., Jannach, D.: Recommending based on rating frequencies: accurate enough? In: Proceedings of the 8th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems at UMAP 2010 (ITWP 2010). pp. 65\u201370 (2010)","DOI":"10.1145\/1864708.1864755"},{"issue":"12","key":"3_CR11","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1145\/138859.138867","volume":"35","author":"D Goldberg","year":"1992","unstructured":"Goldberg, D., Nichols, D., Oki, B.M., Terry, D.: Using collaborative filtering to weave an information tapestry. Commun. ACM 35(12), 61\u201370 (1992)","journal-title":"Commun. ACM"},{"key":"3_CR12","unstructured":"Grozin, V., Levina, A.: Similar product clustering for long-tail cross-sell recommendations. In: AIST (Supplement), pp. 273\u2013280 (2017)"},{"issue":"4","key":"3_CR13","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1145\/2827872","volume":"5","author":"FM Harper","year":"2015","unstructured":"Harper, F.M., Konstan, J.A.: The MovieLens datasets: history and context. ACM Trans. Interact. Intell. Syst. 5(4), 191\u20131919 (2015). http:\/\/doi.acm.org\/10.1145\/2827872","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"3_CR14","doi-asserted-by":"crossref","unstructured":"Herlocker, J.L., Konstan, J.A., Borchers, A., Riedl, J.: An algorithmic framework for performing collaborative filtering. In: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 230\u2013237. ACM (1999)","DOI":"10.1145\/312624.312682"},{"issue":"1","key":"3_CR15","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1145\/963770.963772","volume":"22","author":"JL Herlocker","year":"2004","unstructured":"Herlocker, J.L., Konstan, J.A., Terveen, L.G., Riedl, J.T.: Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst. (TOIS) 22(1), 5\u201353 (2004)","journal-title":"ACM Trans. Inf. Syst. (TOIS)"},{"issue":"5","key":"3_CR16","doi-asserted-by":"publisher","first-page":"602","DOI":"10.1016\/j.ins.2009.10.016","volume":"180","author":"B Jeong","year":"2010","unstructured":"Jeong, B., Lee, J., Cho, H.: Improving memory-based collaborative filtering via similarity updating and prediction modulation. Inf. Sci. 180(5), 602\u2013612 (2010)","journal-title":"Inf. Sci."},{"key":"3_CR17","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.swevo.2017.04.004","volume":"36","author":"R Katarya","year":"2017","unstructured":"Katarya, R., Verma, O.P.: Effectual recommendations using artificial algae algorithm and fuzzy c-mean. Swarm Evol. Comput. 36, 52\u201361 (2017)","journal-title":"Swarm Evol. Comput."},{"issue":"1\u20132","key":"3_CR18","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1007\/s11257-011-9112-x","volume":"22","author":"JA Konstan","year":"2012","unstructured":"Konstan, J.A., Riedl, J.: Recommender systems: from algorithms to user experience. User Model. User-Adap. Inter. 22(1\u20132), 101\u2013123 (2012)","journal-title":"User Model. User-Adap. Inter."},{"issue":"8","key":"3_CR19","doi-asserted-by":"publisher","first-page":"1904","DOI":"10.1109\/TKDE.2012.119","volume":"25","author":"YJ Park","year":"2013","unstructured":"Park, Y.J.: The adaptive clustering method for the long tail problem of recommender systems. IEEE Trans. Knowl. Data Eng. 25(8), 1904\u20131915 (2013)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"3_CR20","doi-asserted-by":"crossref","unstructured":"Park, Y.J., Tuzhilin, A.: The long tail of recommender systems and how to leverage it. In: Proceedings of the 2008 ACM Conference on Recommender Systems, pp. 11\u201318. ACM (2008)","DOI":"10.1145\/1454008.1454012"},{"key":"3_CR21","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1016\/j.eswa.2015.11.023","volume":"48","author":"N Polatidis","year":"2016","unstructured":"Polatidis, N., Georgiadis, C.K.: A multi-level collaborative filtering method that improves recommendations. Expert Syst. Appl. 48, 100\u2013110 (2016)","journal-title":"Expert Syst. Appl."},{"key":"3_CR22","doi-asserted-by":"crossref","unstructured":"Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: Grouplens: an open architecture for collaborative filtering of netnews. In: Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work, pp. 175\u2013186. ACM (1994)","DOI":"10.1145\/192844.192905"},{"key":"3_CR23","doi-asserted-by":"crossref","unstructured":"Shen, K., Liu, Y., Zhang, Z.: Modified similarity algorithm for collaborative filtering. In: International Conference on Knowledge Management in Organizations, pp. 378\u2013385. Springer (2017)","DOI":"10.1007\/978-3-319-62698-7_31"},{"issue":"1","key":"3_CR24","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1145\/2556270","volume":"47","author":"Y Shi","year":"2014","unstructured":"Shi, Y., Larson, M., Hanjalic, A.: Collaborative filtering beyond the user-item matrix: a survey of the state of the art and future challenges. ACM Comput. Surv. (CSUR) 47(1), 3 (2014)","journal-title":"ACM Comput. Surv. (CSUR)"},{"issue":"8","key":"3_CR25","doi-asserted-by":"publisher","first-page":"e0183570","DOI":"10.1371\/journal.pone.0183570","volume":"12","author":"SB Sun","year":"2017","unstructured":"Sun, S.B., Zhang, Z.H., Dong, X.L., Zhang, H.R., Li, T.J., Zhang, L., Min, F.: Integrating triangle and jaccard similarities for recommendation. PloS One 12(8), e0183570 (2017)","journal-title":"PloS One"},{"key":"3_CR26","doi-asserted-by":"publisher","first-page":"27211","DOI":"10.1109\/ACCESS.2017.2778424","volume":"5","author":"Z Tan","year":"2017","unstructured":"Tan, Z., He, L.: An efficient similarity measure for user-based collaborative filtering recommender systems inspired by the physical resonance principle. IEEE Access 5, 27211\u201327228 (2017)","journal-title":"IEEE Access"},{"key":"3_CR27","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/j.elerap.2016.01.003","volume":"18","author":"S Wei","year":"2016","unstructured":"Wei, S., Zheng, X., Chen, D., Chen, C.: A hybrid approach for movie recommendation via tags and ratings q. Electron. Commer. Res. Appl. 18, 83\u201394 (2016)","journal-title":"Electron. Commer. Res. Appl."},{"issue":"9","key":"3_CR28","doi-asserted-by":"publisher","first-page":"896","DOI":"10.14778\/2311906.2311916","volume":"5","author":"H Yin","year":"2012","unstructured":"Yin, H., Cui, B., Li, J., Yao, J., Chen, C.: Challenging the long tail recommendation. Proc. VLDB Endowment 5(9), 896\u2013907 (2012). http:\/\/dl.acm.org\/citation.cfm?id=2311916","journal-title":"Proc. VLDB Endowment"}],"container-title":["Advances in Intelligent Systems and Computing","Intelligent Systems and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-29516-5_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,19]],"date-time":"2023-09-19T11:42:32Z","timestamp":1695123752000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-29516-5_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,24]]},"ISBN":["9783030295158","9783030295165"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-29516-5_3","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2019,8,24]]},"assertion":[{"value":"24 August 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IntelliSys","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Proceedings of SAI Intelligent Systems Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"London","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 September 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 September 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"intellisys2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/saiconference.com\/IntelliSys","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}