TY - CHAP

T1 - Supervised clustering of streaming data for email batch detection

AU - Haider, Peter

AU - Brefeld, Ulf

AU - Scheffer, Tobias

N1 - Conference code: 24

PY - 2007

Y1 - 2007

N2 - We address the problem of detecting batches of emails that have been created according to the same template. This problem is motivated by the desire to filter spam more effectively by exploiting collective information about entire batches of jointly generated messages. The application matches the problem setting of supervised clustering, because examples of correct clusterings can be collected. Known decoding procedures for supervised clustering are cubic in the number of instances. When decisions cannot be reconsidered once they have been made - - owing to the streaming nature of the data - - then the decoding problem can be solved in linear time. We devise a sequential decoding procedure and derive the corresponding optimization problem of supervised clustering. We study the impact of collective attributes of email batches on the effectiveness of recognizing spam emails.

AB - We address the problem of detecting batches of emails that have been created according to the same template. This problem is motivated by the desire to filter spam more effectively by exploiting collective information about entire batches of jointly generated messages. The application matches the problem setting of supervised clustering, because examples of correct clusterings can be collected. Known decoding procedures for supervised clustering are cubic in the number of instances. When decisions cannot be reconsidered once they have been made - - owing to the streaming nature of the data - - then the decoding problem can be solved in linear time. We devise a sequential decoding procedure and derive the corresponding optimization problem of supervised clustering. We study the impact of collective attributes of email batches on the effectiveness of recognizing spam emails.

KW - Informatics

KW - Business informatics

UR - http://www.scopus.com/inward/record.url?scp=34547983265&partnerID=8YFLogxK

U2 - 10.1145/1273496.1273540

DO - 10.1145/1273496.1273540

M3 - Article in conference proceedings

AN - SCOPUS:34547983265

SN - 978-1-59593-793-3

SP - 345

EP - 352

BT - Proceedings of the 24th international conference on Machine learning

A2 - Ghahramani, Zoubin

PB - Association for Computing Machinery, Inc

CY - New York

T2 - Proceedings of the 24th international conference on Machine learning - ICML 2007

Y2 - 20 June 2007 through 24 June 2007

ER -