{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:20:08Z","timestamp":1750306808410,"version":"3.41.0"},"reference-count":29,"publisher":"Association for Computing Machinery (ACM)","issue":"4","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. Knowl. Discov. Data"],"published-print":{"date-parts":[[2013,11]]},"abstract":"<jats:p>Classification in Peer-to-Peer (P2P) networks is important to many real applications, such as distributed intrusion detection, distributed recommendation systems, and distributed antispam detection. However, it is very challenging to perform classification in P2P networks due to many practical issues, such as scalability, peer dynamism, and asynchronism. This article investigates the practical techniques of constructing Support Vector Machine (SVM) classifiers in the P2P networks. In particular, we demonstrate how to efficiently cascade SVM in a P2P network with the use of reduced SVM. In addition, we propose to fuse the concept of cascade SVM with bootstrap aggregation to effectively balance the trade-off between classification accuracy, model construction, and prediction cost. We provide theoretical insights for the proposed solutions and conduct an extensive set of empirical studies on a number of large-scale datasets. Encouraging results validate the efficacy of the proposed approach.<\/jats:p>","DOI":"10.1145\/2541268.2541273","type":"journal-article","created":{"date-parts":[[2014,1,6]],"date-time":"2014-01-06T20:42:39Z","timestamp":1389040959000},"page":"1-29","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Classification in P2P networks with cascade support vector machines"],"prefix":"10.1145","volume":"7","author":[{"given":"Hock Hee","family":"Ang","sequence":"first","affiliation":[{"name":"Nanyang Technological University, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vivekanand","family":"Gopalkrishnan","sequence":"additional","affiliation":[{"name":"Deloitte Analytics Institute Asia, Robinson Road, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Steven C. H.","family":"Hoi","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wee Keong","family":"Ng","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2013,12,25]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/3120828.3120854"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-12026-8_5"},{"volume-title":"6th International Workshops (DBISP2P'08)","author":"Ang H. H.","key":"e_1_2_1_3_1","unstructured":"Ang , H. H. , Gopalkrishnan , V. , Hoi , S. C. H. , Ng , W. K. , and Datta , A . 2008b. Classification in P2P networks by bagging cascade RSVMs. In Databases, Information Systems, and Peer-to-Peer Computing , 6th International Workshops (DBISP2P'08) . 13--25. Ang, H. H., Gopalkrishnan, V., Hoi, S. C. H., Ng, W. K., and Datta, A. 2008b. Classification in P2P networks by bagging cascade RSVMs. In Databases, Information Systems, and Peer-to-Peer Computing, 6th International Workshops (DBISP2P'08). 13--25."},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.5555\/3121576.3121603"},{"volume-title":"Proceedings of the 2010 European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (ECML PKDD'10). 24--39","author":"Ang H. H.","key":"e_1_2_1_5_1","unstructured":"Ang , H. H. , Gopalkrishnan , V. , Ng , W. K. , and Hoi , S. C. H. 2010b. On classifying drifting concepts in P2P networks . In Proceedings of the 2010 European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (ECML PKDD'10). 24--39 . Ang, H. H., Gopalkrishnan, V., Ng, W. K., and Hoi, S. C. H. 2010b. On classifying drifting concepts in P2P networks. 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Distributed pasting of small votes. In Proceedings of the 3rd International Workshop on Multiple Classifier Systems (MCS'02). 52--61."},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIC.2006.74"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1023\/B:MACH.0000015881.36452.6e"},{"key":"e_1_2_1_15_1","unstructured":"Graf H. P. Cosatto E. Bottou L. Dourdanovic I. and Vapnik V. 2004. Parallel support vector machines: The cascade SVM. In Saul L. K. Weiss Y. and Bottou L. (Eds.). Neural Information Processing Systems. MIT Press Cambridge MA 521--528.  Graf H. P. Cosatto E. Bottou L. Dourdanovic I. and Vapnik V. 2004. Parallel support vector machines: The cascade SVM. In Saul L. K. Weiss Y. and Bottou L. (Eds.). Neural Information Processing Systems. 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