{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T22:01:45Z","timestamp":1780610505810,"version":"3.54.1"},"reference-count":47,"publisher":"Association for Computing Machinery (ACM)","issue":"5","license":[{"start":{"date-parts":[[2017,6,30]],"date-time":"2017-06-30T00:00:00Z","timestamp":1498780800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Australian Research Council (ARC) Discovery Early Career Researcher Award","award":["DE160100509"],"award-info":[{"award-number":["DE160100509"]}]},{"name":"ARC Future Fellowship","award":["FT140101247"],"award-info":[{"award-number":["FT140101247"]}]},{"name":"Discovery Project","award":["DP140100104"],"award-info":[{"award-number":["DP140100104"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Intell. Syst. Technol."],"published-print":{"date-parts":[[2017,9,30]]},"abstract":"<jats:p>\n                    With recent advances in radio-frequency identification (RFID), wireless sensor networks, and Web services, physical things are becoming an integral part of the emerging ubiquitous Web. Finding correlations among ubiquitous things is a crucial prerequisite for many important applications such as things search, discovery, classification, recommendation, and composition. This article presents\n                    <jats:bold>DisCor-T<\/jats:bold>\n                    , a novel graph-based approach for discovering\n                    <jats:italic toggle=\"yes\">underlying connections<\/jats:italic>\n                    of things via mining the rich content embodied in the human-thing interactions in terms of user, temporal, and spatial information. We model this various information using two graphs, namely a spatio-temporal graph and a social graph. Then, random walk with restart (RWR) is applied to find proximities among things, and a relational graph of things (RGT) indicating implicit correlations of things is learned. The correlation analysis lays a solid foundation contributing to improved effectiveness in things management and analytics. To demonstrate the utility of the proposed approach, we develop a flexible feature-based classification framework on top of RGT and perform a systematic case study. Our evaluation exhibits the strength and feasibility of the proposed approach.\n                  <\/jats:p>","DOI":"10.1145\/3035967","type":"journal-article","created":{"date-parts":[[2017,6,30]],"date-time":"2017-06-30T13:44:59Z","timestamp":1498830299000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Unveiling Correlations via Mining Human-Thing Interactions in the Web of Things"],"prefix":"10.1145","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4149-839X","authenticated-orcid":false,"given":"Lina","family":"Yao","sequence":"first","affiliation":[{"name":"UNSW Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quan Z.","family":"Sheng","sequence":"additional","affiliation":[{"name":"Macquarie University, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anne H. H.","family":"Ngu","sequence":"additional","affiliation":[{"name":"The Texas State University, TX"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xue","family":"Li","sequence":"additional","affiliation":[{"name":"The University of Queensland, Queensland, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Boualem","family":"Benattalah","sequence":"additional","affiliation":[{"name":"UNSW Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2017,6,30]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/1182635.1164243"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1148170.1148254"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIC.2015.31"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2013.142"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1961189.1961199"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSC.2011.69"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSC.2011.69"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/MPRV.2011.78"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-19157-2_5"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1137\/S106482750240265X"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/1014052.1014125"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1037\/0022-3514.73.2.296"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1016591616731"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/2396761.2398474"},{"key":"e_1_2_1_15_1","volume-title":"Proceedings of the Semantic Web Challenge.","author":"Le-Phuoc Danh","year":"2011","unstructured":"Danh Le-Phuoc, Hoan Nguyen Mau Quoc, Josiane Xavier Parreira, and Manfred Hauswirth. 2011. The linked sensor middleware--Connecting the real world and the semantic web. In Proceedings of the Semantic Web Challenge."},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273558"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.100.118703"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.5555\/1597538.1597606"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-34952-2_1"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.3390\/jsan2020172"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.5555\/2984093.2984237"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2007.250"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/1090193.1090201"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.74.036104"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.69.026113"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1023\/B:WINE.0000044029.06344.dd"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.5555\/2318776.2318787"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/0306-4573(88)90021-0"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2010.51"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2008.386"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/2124295.2124373"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/1721695.1721709"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557109"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2006.70"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1142\/S0218843014500014"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/1007568.1007586"},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2008.196"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/2247596.2247672"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2013.99"},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2009.134"},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/2396761.2398470"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIC.2015.77"},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2013.87"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/2837024"},{"key":"e_1_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020491"},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","unstructured":"Yu Zhang and Dit Yan Yeung. 2011. Multi-task learning in heterogeneous feature spaces. In Proceedings of the 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference (AAAI-11\/IAAI-1111) Code 87049 Proceedings of the National Conference on Artificial Intelligence.","DOI":"10.5555\/2900423.2900515"},{"key":"e_1_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.5555\/3041838.3041953"}],"container-title":["ACM Transactions on Intelligent Systems and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3035967","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3035967","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T21:01:39Z","timestamp":1780606899000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3035967"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,6,30]]},"references-count":47,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2017,9,30]]}},"alternative-id":["10.1145\/3035967"],"URL":"https:\/\/doi.org\/10.1145\/3035967","relation":{},"ISSN":["2157-6904","2157-6912"],"issn-type":[{"value":"2157-6904","type":"print"},{"value":"2157-6912","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,6,30]]},"assertion":[{"value":"2016-01-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2016-12-01","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2017-06-30","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}