{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T07:34:19Z","timestamp":1791272059408,"version":"4.1.0"},"reference-count":11,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2005,12,1]],"date-time":"2005-12-01T00:00:00Z","timestamp":1133395200000},"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":["SIGKDD Explor. Newsl."],"published-print":{"date-parts":[[2005,12]]},"abstract":"<jats:p>\n            In this paper, we describe the challenges inherent to the task of\n            <jats:italic>link prediction<\/jats:italic>\n            , and we analyze one reason why many link prediction models perform poorly. Specifically, we demonstrate the effects of the extremely large class skew associated with the link prediction task. We then present an alternate task ---\n            <jats:italic>anomalous link discovery<\/jats:italic>\n            (ALD) --- and qualitatively demonstrate the effectiveness of simple link prediction models for the ALD task. We show that even the simplistic structural models that perform poorly on link prediction can perform quite well at the ALD task.\n          <\/jats:p>","DOI":"10.1145\/1117454.1117460","type":"journal-article","created":{"date-parts":[[2007,1,17]],"date-time":"2007-01-17T18:32:02Z","timestamp":1169058722000},"page":"41-47","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":82,"title":["The case for anomalous link discovery"],"prefix":"10.1145","volume":"7","author":[{"given":"Matthew J.","family":"Rattigan","sequence":"first","affiliation":[{"name":"University of Massachusetts, Amherst, MA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Jensen","sequence":"additional","affiliation":[{"name":"University of Massachusetts, Amherst, MA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2005,12]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1014052.1014068"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1009778005914"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/959242.959253"},{"key":"e_1_2_1_4_1","volume-title":"Journal of Machine Learning Research","author":"Getoor L.","year":"2003"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/956750.956794"},{"key":"e_1_2_1_6_1","volume-title":"Proceedings of the Seventh USENIX Security Symposium (SECURITY '98)","author":"Lee W.","year":"1998"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/956863.956972"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.5555\/951949.952188"},{"key":"e_1_2_1_9_1","volume-title":"Proceedings of the National Science Foundation Workshop on Next Generation Data Mining","author":"Mooney R.","year":"2002"},{"key":"e_1_2_1_10_1","volume-title":"Statistical Relational Learning For Link Prediction. Workshop on Learning Statistical Models from Relational Data at IJCAI","author":"Popescul A.","year":"2003"},{"key":"e_1_2_1_11_1","volume-title":"Link Prediction in Relational Data. Neural Information Processing Systems Conference (NIPS)","author":"Taskar B.","year":"2003"}],"container-title":["ACM SIGKDD Explorations Newsletter"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1117454.1117460","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/1117454.1117460","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T16:18:45Z","timestamp":1750263525000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1117454.1117460"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2005,12]]},"references-count":11,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2005,12]]}},"alternative-id":["10.1145\/1117454.1117460"],"URL":"https:\/\/doi.org\/10.1145\/1117454.1117460","relation":{},"ISSN":["1931-0145","1931-0153"],"issn-type":[{"value":"1931-0145","type":"print"},{"value":"1931-0153","type":"electronic"}],"subject":[],"published":{"date-parts":[[2005,12]]},"assertion":[{"value":"2005-12-01","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}