{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T12:14:18Z","timestamp":1763468058787,"version":"3.41.0"},"reference-count":43,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2012,1,1]],"date-time":"2012-01-01T00:00:00Z","timestamp":1325376000000},"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. Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2012,1]]},"abstract":"<jats:p>In this article, we present a novel algorithm to discover multirelational structures from social media streams. A media item such as a photograph exists as part of a meaningful interrelationship among several attributes, including time, visual content, users, and actions. Discovery of such relational structures enables us to understand the semantics of human activity and has applications in content organization, recommendation algorithms, and exploratory social network analysis.<\/jats:p>\n          <jats:p>We are proposing a novel nonnegative matrix factorization framework to characterize relational structures of group photo streams. The factorization incorporates image content features and contextual information. The idea is to consider a cluster as having similar relational patterns; each cluster consists of photos relating to similar content or context. Relations represent different aspects of the photo stream data, including visual content, associated tags, photo owners, and post times. The extracted structures minimize the mutual information of the predicted joint distribution. We also introduce a relational modularity function to determine the structure cost penalty, and hence determine the number of clusters. Extensive experiments on a large Flickr dataset suggest that our approach is able to extract meaningful relational patterns from group photo streams. We evaluate the utility of the discovered structures through a tag prediction task and through a user study. Our results show that our method based on relational structures, outperforms baseline methods, including feature and tag frequency based techniques, by 35%--420%. We have conducted a qualitative user study to evaluate the benefits of our framework in exploring group photo streams. The study indicates that users found the extracted clustering results clearly represent major themes in a group; the clustering results not only reflect how users describe the group data but often lead the users to discover the evolution of the group activity.<\/jats:p>","DOI":"10.1145\/2071396.2071400","type":"journal-article","created":{"date-parts":[[2012,1,31]],"date-time":"2012-01-31T14:49:20Z","timestamp":1328021360000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Discovering multirelational structure in social media streams"],"prefix":"10.1145","volume":"8","author":[{"given":"Yu-Ru","family":"Lin","sequence":"first","affiliation":[{"name":"Arizona State University"}]},{"given":"Hari","family":"Sundaram","sequence":"additional","affiliation":[{"name":"Arizona State University"}]},{"given":"Munmun","family":"De Choudhury","sequence":"additional","affiliation":[{"name":"Arizona State University"}]},{"given":"Aisling","family":"Kelliher","sequence":"additional","affiliation":[{"name":"Arizona State University"}]}],"member":"320","published-online":{"date-parts":[[2012,2,3]]},"reference":[{"doi-asserted-by":"publisher","key":"e_1_2_1_1_1","DOI":"10.1145\/1255175.1255177"},{"doi-asserted-by":"publisher","key":"e_1_2_1_2_1","DOI":"10.1145\/1150402.1150412"},{"volume-title":"Proceedings of the SIAM International Conference on Data Mining.","author":"Banerjee A.","unstructured":"Banerjee , A. , Basu , S. , and Merugu , S . 2007. Multi-way clustering on relation graphs . In Proceedings of the SIAM International Conference on Data Mining. Banerjee, A., Basu, S., and Merugu, S. 2007. Multi-way clustering on relation graphs. In Proceedings of the SIAM International Conference on Data Mining.","key":"e_1_2_1_3_1"},{"doi-asserted-by":"publisher","key":"e_1_2_1_4_1","DOI":"10.1145\/1102351.1102357"},{"doi-asserted-by":"publisher","key":"e_1_2_1_5_1","DOI":"10.5555\/944919.944937"},{"doi-asserted-by":"publisher","key":"e_1_2_1_6_1","DOI":"10.1145\/1143844.1143859"},{"doi-asserted-by":"publisher","key":"e_1_2_1_7_1","DOI":"10.1145\/1027527.1027747"},{"doi-asserted-by":"publisher","key":"e_1_2_1_8_1","DOI":"10.1145\/1459359.1459473"},{"doi-asserted-by":"publisher","key":"e_1_2_1_9_1","DOI":"10.1145\/956750.956764"},{"unstructured":"Doreian P. and Fujimoto K. 2001. Structures of supreme court voting. University of Pittsburgh manuscript version November 3: 2001.  Doreian P. and Fujimoto K. 2001. Structures of supreme court voting. University of Pittsburgh manuscript version November 3: 2001.","key":"e_1_2_1_10_1"},{"doi-asserted-by":"publisher","key":"e_1_2_1_11_1","DOI":"10.1145\/1454008.1454020"},{"doi-asserted-by":"publisher","key":"e_1_2_1_12_1","DOI":"10.1145\/345508.345545"},{"doi-asserted-by":"publisher","key":"e_1_2_1_13_1","DOI":"10.1073\/pnas.0802631105"},{"doi-asserted-by":"publisher","key":"e_1_2_1_14_1","DOI":"10.1145\/1291233.1291384"},{"volume-title":"Proceedings of the 8th International Conference on Inductive Logic Programming. 261","author":"Kirsten M.","unstructured":"Kirsten , M. and Wrobel , S . 1998. Relational distance-based clustering . In Proceedings of the 8th International Conference on Inductive Logic Programming. 261 . Kirsten, M. and Wrobel, S. 1998. Relational distance-based clustering. In Proceedings of the 8th International Conference on Inductive Logic Programming. 261.","key":"e_1_2_1_15_1"},{"doi-asserted-by":"publisher","key":"e_1_2_1_16_1","DOI":"10.1145\/1150402.1150476"},{"volume-title":"Proceedings of the Conference on Advances in Neural Information Processing Systems. 556--562","author":"Lee D.","unstructured":"Lee , D. and Seung , H . 2001. Algorithms for non-negative matrix factorization . In Proceedings of the Conference on Advances in Neural Information Processing Systems. 556--562 . Lee, D. and Seung, H. 2001. Algorithms for non-negative matrix factorization. In Proceedings of the Conference on Advances in Neural Information Processing Systems. 556--562.","key":"e_1_2_1_17_1"},{"doi-asserted-by":"publisher","key":"e_1_2_1_18_1","DOI":"10.1145\/1321440.1321463"},{"doi-asserted-by":"publisher","key":"e_1_2_1_19_1","DOI":"10.1145\/1367497.1367590"},{"volume-title":"Proceedings of the IEEE International Conference on Multimedia and Expo (ICME'09)","author":"Lin Y.-R.","unstructured":"Lin , Y.-R. , Sundaram , H. , De Choudhury , M. , and Kelliher , A . 2009a. Temporal patterns in social media streams: Theme discovery and evolution using joint analysis of content and context . In Proceedings of the IEEE International Conference on Multimedia and Expo (ICME'09) . Lin, Y.-R., Sundaram, H., De Choudhury, M., and Kelliher, A. 2009a. Temporal patterns in social media streams: Theme discovery and evolution using joint analysis of content and context. In Proceedings of the IEEE International Conference on Multimedia and Expo (ICME'09).","key":"e_1_2_1_20_1"},{"volume-title":"Proceedings of the International Conference on Weblogs and Social Media.","author":"Lin Y.-R.","unstructured":"Lin , Y.-R. , Sundaram , H. , and Kelliher , A . 2009b. Jam: Joint action matrix factorization for summarizing a temporal heterogeneous social network . In Proceedings of the International Conference on Weblogs and Social Media. Lin, Y.-R., Sundaram, H., and Kelliher, A. 2009b. Jam: Joint action matrix factorization for summarizing a temporal heterogeneous social network. In Proceedings of the International Conference on Weblogs and Social Media.","key":"e_1_2_1_21_1"},{"doi-asserted-by":"publisher","key":"e_1_2_1_22_1","DOI":"10.1016\/j.patrec.2006.06.019"},{"doi-asserted-by":"publisher","key":"e_1_2_1_23_1","DOI":"10.1145\/1150402.1150439"},{"doi-asserted-by":"publisher","key":"e_1_2_1_24_1","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"doi-asserted-by":"publisher","key":"e_1_2_1_25_1","DOI":"10.1109\/TPAMI.2003.1217601"},{"doi-asserted-by":"publisher","key":"e_1_2_1_26_1","DOI":"10.1109\/TPAMI.2005.49"},{"doi-asserted-by":"publisher","key":"e_1_2_1_27_1","DOI":"10.1145\/1386352.1386406"},{"doi-asserted-by":"publisher","key":"e_1_2_1_28_1","DOI":"10.1103\/PhysRevE.69.026113"},{"unstructured":"Palla G. Barabasi A. and Vicsek T. 2007. Quantifying social group evolution. eprint arXiv: 0704.0744.  Palla G. Barabasi A. and Vicsek T. 2007. Quantifying social group evolution. eprint arXiv: 0704.0744.","key":"e_1_2_1_29_1"},{"doi-asserted-by":"publisher","key":"e_1_2_1_30_1","DOI":"10.1145\/1367497.1367541"},{"doi-asserted-by":"publisher","key":"e_1_2_1_31_1","DOI":"10.1145\/564376.564421"},{"doi-asserted-by":"publisher","key":"e_1_2_1_32_1","DOI":"10.1145\/1290082.1290120"},{"doi-asserted-by":"publisher","key":"e_1_2_1_33_1","DOI":"10.1145\/1367497.1367542"},{"doi-asserted-by":"publisher","key":"e_1_2_1_34_1","DOI":"10.1177\/030631289019003001"},{"doi-asserted-by":"publisher","key":"e_1_2_1_35_1","DOI":"10.1145\/1281192.1281266"},{"doi-asserted-by":"publisher","key":"e_1_2_1_36_1","DOI":"10.1145\/1401890.1401972"},{"doi-asserted-by":"publisher","key":"e_1_2_1_37_1","DOI":"10.1145\/1101149.1101337"},{"doi-asserted-by":"publisher","key":"e_1_2_1_38_1","DOI":"10.1145\/1150402.1150450"},{"doi-asserted-by":"publisher","key":"e_1_2_1_39_1","DOI":"10.1145\/1148170.1148214"},{"doi-asserted-by":"publisher","key":"e_1_2_1_40_1","DOI":"10.1016\/j.patrec.2005.02.003"},{"volume-title":"Proceedings of the International Conference on Acoustics, Speech, and Signal Processing. IEEE, 4096--4099","author":"Xie L.","unstructured":"Xie , L. , Chang , S. , Divakaran , A. , and Sun , H . 2002. Structure analysis of soccer video with hidden markov models . In Proceedings of the International Conference on Acoustics, Speech, and Signal Processing. IEEE, 4096--4099 . Xie, L., Chang, S., Divakaran, A., and Sun, H. 2002. Structure analysis of soccer video with hidden markov models. In Proceedings of the International Conference on Acoustics, Speech, and Signal Processing. IEEE, 4096--4099.","key":"e_1_2_1_41_1"},{"doi-asserted-by":"publisher","key":"e_1_2_1_42_1","DOI":"10.1145\/1277741.1277825"},{"doi-asserted-by":"publisher","key":"e_1_2_1_43_1","DOI":"10.1145\/1291233.1291382"}],"container-title":["ACM Transactions on Multimedia Computing, Communications, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2071396.2071400","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2071396.2071400","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T10:06:22Z","timestamp":1750241182000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2071396.2071400"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,1]]},"references-count":43,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2012,1]]}},"alternative-id":["10.1145\/2071396.2071400"],"URL":"https:\/\/doi.org\/10.1145\/2071396.2071400","relation":{},"ISSN":["1551-6857","1551-6865"],"issn-type":[{"type":"print","value":"1551-6857"},{"type":"electronic","value":"1551-6865"}],"subject":[],"published":{"date-parts":[[2012,1]]},"assertion":[{"value":"2009-08-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2010-08-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2012-02-03","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}