{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T13:01:50Z","timestamp":1773406910571,"version":"3.50.1"},"reference-count":42,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2013,11,1]],"date-time":"2013-11-01T00:00:00Z","timestamp":1383264000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Internet Technol."],"published-print":{"date-parts":[[2013,11]]},"abstract":"<jats:p>\n            The extraordinary technological progress we have witnessed in recent years has made it possible to generate and exchange multimedia content at an unprecedented rate. As a consequence, massive collections of multimedia objects are now widely available to a large population of users. As the task of browsing such large collections could be daunting,\n            <jats:italic>Recommender Systems<\/jats:italic>\n            are being developed to assist users in finding items that match their needs and preferences. In this article, we present a novel approach to recommendation in multimedia browsing systems, based on modeling recommendation as a social choice problem. In social choice theory, a set of voters is called to rank a set of alternatives, and individual rankings are aggregated into a global ranking. In our formulation, the set of voters and the set of alternatives both coincide with the set of objects in the data collection. We first define what constitutes a choice in the browsing domain and then define a mechanism to aggregate individual choices into a global ranking. The result is a framework for computing customized recommendations by originally combining intrinsic features of multimedia objects, past behavior of individual users, and overall behavior of the entire community of users. Recommendations are ranked using an importance ranking algorithm that resembles the well-known\n            <jats:italic>PageRank<\/jats:italic>\n            strategy. Experiments conducted on a prototype of the proposed system confirm the effectiveness and efficiency of our approach.\n          <\/jats:p>","DOI":"10.1145\/2532640","type":"journal-article","created":{"date-parts":[[2013,12,4]],"date-time":"2013-12-04T14:04:47Z","timestamp":1386165887000},"page":"1-32","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":72,"title":["A Multimedia Recommender System"],"prefix":"10.1145","volume":"13","author":[{"given":"Massimiliano","family":"Albanese","sequence":"first","affiliation":[{"name":"George Mason University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antonio","family":"d\u2019Acierno","sequence":"additional","affiliation":[{"name":"ISA - CNR"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vincenzo","family":"Moscato","sequence":"additional","affiliation":[{"name":"University of Naples"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fabio","family":"Persia","sequence":"additional","affiliation":[{"name":"University of Naples"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antonio","family":"Picariello","sequence":"additional","affiliation":[{"name":"University of Naples"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2013,11]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.99"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1864708.1864722"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-010-0480-8"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1816041.1816087"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1278366.1278371"},{"key":"e_1_2_1_6_1","volume-title":"Social Choice and Individual Values","author":"Arrow K. 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Evaluation of recommender algorithms for an internet information broker based on simple association rules and on the repeat-buying theory. In Proceedings of the 4th International Workshop on Mining Web Data for Discovering Usage Patterns and Profiles (WEBKDD). 100--114."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/963770.963772"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/1141277.1141526"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557067"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/1864708.1864727"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.2478\/v10006-009-0015-5"},{"key":"e_1_2_1_20_1","first-page":"12","article-title":"Personalized integration of recommendation methods for e-commerce","volume":"3","author":"Kazienko P.","year":"2006","unstructured":"Kazienko , P. and Kolodziejski , P. 2006 . 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Ontology-based recommendation in multimedia sharing systems . Syst. Sci. 34 , 1, 97 -- 106 . Musial, K., Juszczyszyn, K., and Kazienko, P. 2008. Ontology-based recommendation in multimedia sharing systems. Syst. Sci. 34, 1, 97--106.","journal-title":"Syst. Sci."},{"key":"e_1_2_1_31_1","unstructured":"Page L. Brin S. Motwani R. and Winograd T. 1999. The PageRank citation ranking: Bringing order to the web. Tech. rep. 1999-66 Stanford InfoLab.  Page L. Brin S. Motwani R. and Winograd T. 1999. The PageRank citation ranking: Bringing order to the web. Tech. rep. 1999-66 Stanford InfoLab."},{"key":"e_1_2_1_32_1","doi-asserted-by":"crossref","unstructured":"Pazzani M. J.\n     and \n      Billsus D\n  . \n  2007\n  . Content-based recommendation systems. In The Adaptive Web Lecture Notes in Computer Science Series vol. \n  4321 Springer 325--341.   Pazzani M. J. and Billsus D. 2007. Content-based recommendation systems. 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