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Knowl. Discov. Data"],"published-print":{"date-parts":[[2018,6,30]]},"abstract":"<jats:p>\n            Given a large-scale and high-order tensor, how can we detect dense subtensors in it? Can we spot them in near-linear time but with quality guarantees? Extensive previous work has shown that dense subtensors, as well as dense subgraphs, indicate anomalous or fraudulent behavior (e.g., lockstep behavior in social networks). However, available algorithms for detecting dense subtensors are not satisfactory in terms of speed, accuracy, and flexibility. In this work, we propose two algorithms, called M-Z\n            <jats:sc>oom<\/jats:sc>\n            and M-B\n            <jats:sc>iz<\/jats:sc>\n            , for fast and accurate dense-subtensor detection with various density measures. M-Z\n            <jats:sc>oom<\/jats:sc>\n            gives a lower bound on the density of detected subtensors, while M-B\n            <jats:sc>iz<\/jats:sc>\n            guarantees the local optimality of detected subtensors. M-Z\n            <jats:sc>oom<\/jats:sc>\n            and M-B\n            <jats:sc>iz<\/jats:sc>\n            can be combined, giving the following advantages: (1)\n            <jats:italic>Scalable:<\/jats:italic>\n            scale near-linearly with all aspects of tensors and are up to\n            <jats:italic>114\u00d7 faster<\/jats:italic>\n            than state-of-the-art methods with similar accuracy, (2)\n            <jats:italic>Provably accurate<\/jats:italic>\n            : provide a guarantee on the lowest density and local optimality of the subtensors they find, (3)\n            <jats:italic>Flexible:<\/jats:italic>\n            support multi-subtensor detection and size bounds as well as diverse density measures, and (4)\n            <jats:italic>Effective:<\/jats:italic>\n            successfully detected edit wars and bot activities in Wikipedia, and spotted network attacks from a TCP dump with near-perfect accuracy (AUC = 0.98).\n          <\/jats:p>","DOI":"10.1145\/3154414","type":"journal-article","created":{"date-parts":[[2018,1,23]],"date-time":"2018-01-23T14:53:36Z","timestamp":1516719216000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":22,"title":["Fast, Accurate, and Flexible Algorithms for Dense Subtensor Mining"],"prefix":"10.1145","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2872-1526","authenticated-orcid":false,"given":"Kijung","family":"Shin","sequence":"first","affiliation":[{"name":"Carnegie Mellon University, Forbes Avenue, Pittsburgh, PA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5645-1754","authenticated-orcid":false,"given":"Bryan","family":"Hooi","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Forbes Avenue, Pittsburgh, PA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christos","family":"Faloutsos","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Forbes Avenue, Pittsburgh, PA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2018,1,23]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-13672-6_40"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-95995-3_3"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1137\/060676489"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-13123-8_6"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.14778\/2140436.2140442"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2684822.2685298"},{"key":"e_1_2_1_7_1","volume-title":"Proceedings of KDD Cup and Workshop","volume":"2007","author":"Bennett James","year":"2007"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2488388.2488400"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2746539.2746592"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972788.4"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.5555\/646688.702972"},{"key":"e_1_2_1_12_1","volume-title":"Proceedings of KDD Cup","author":"Dror Gideon","year":"2012"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741638"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-016-0464-z"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.5555\/1083592.1083676"},{"key":"e_1_2_1_16_1","volume-title":"Finding a Maximum Density Subgraph","author":"Goldberg Andrew V."},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3056563"},{"key":"e_1_2_1_18_1","volume-title":"Zhukov","author":"Ignatov Dmitry I.","year":"2013"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2015.61"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623632"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-06608-0_11"},{"key":"e_1_2_1_22_1","unstructured":"Ravi Kannan and V. Vinay. 1999. Analyzing the Structure of Large Graphs. Rheinische Friedrich-Wilhelms-Universit\u00e4t Bonn.  Ravi Kannan and V. Vinay. 1999. Analyzing the Structure of Large Graphs. Rheinische Friedrich-Wilhelms-Universit\u00e4t Bonn."},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-02927-1_50"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1137\/07070111X"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487788.2488173"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-6045-0_10"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASONAM.2011.80"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783381"},{"key":"e_1_2_1_29_1","volume-title":"Vu","author":"McGregor Andrew","year":"2015"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/1298306.1298311"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/1242572.1242600"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-13672-6_42"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/1014052.1014140"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2014.36"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0058"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46128-1_17"},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3018661.3018676"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098087"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2487645"}],"container-title":["ACM Transactions on Knowledge Discovery from Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3154414","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3154414","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3154414","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:11:26Z","timestamp":1750212686000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3154414"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,1,23]]},"references-count":39,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2018,6,30]]}},"alternative-id":["10.1145\/3154414"],"URL":"https:\/\/doi.org\/10.1145\/3154414","relation":{},"ISSN":["1556-4681","1556-472X"],"issn-type":[{"value":"1556-4681","type":"print"},{"value":"1556-472X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,1,23]]},"assertion":[{"value":"2016-12-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2017-10-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2018-01-23","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}