OPTICS-Based Clustering of Emails Represented by Quantitative Profiles
作者： Vladimír Špitalský , Marian Grendár
DOI: 10.1007/978-3-319-00551-5_7
关键词:
摘要: OPTICS (Ordering Points To Identify the Clustering Structure) is an algorithm for finding density-based clusters in data.We introduce adaptive dynamical clustering based on OPTICS. The applied to emails which are represented by quantitative profiles. Performance of assessed public email corpuses TREC and CEAS.
springer.com
sci-hub.st 参考文章(21)
Tiago A. Almeida, Akebo Yamakami, Advances in Spam Filtering Techniques Computational Intelligence for Privacy and Security. pp. 199- 214 ,(2012) , 10.1007/978-3-642-25237-2_12
Romit Roy Choudhury, Haifeng Yu, Vikram Srinivasan, Nitin H. Vaidya, Marcos K. Aguilera, Distributed Computing and Networking ,(2008)
Elke Achtert, Christian Böhm, Peer Kröger, DeLi-Clu: boosting robustness, completeness, usability, and efficiency of hierarchical clustering by a closest pair ranking knowledge discovery and data mining. pp. 119- 128 ,(2006) , 10.1007/11731139_16
Paul Sroufe, Santi Phithakkitnukoon, Ram Dantu, João Cangussu, Email shape analysis international conference of distributed computing and networking. pp. 18- 29 ,(2010) , 10.1007/978-3-642-11322-2_7
Jörg Sander, Nan Niu, Zhiyong Lu, Alex Kovarsky, Xuejie Qin, Automatic extraction of clusters from hierarchical clustering representations knowledge discovery and data mining. pp. 75- 87 ,(2003) , 10.5555/1760894.1760906
Vladimir Spitalský, Marian Grendár, Jana Skutová, Spam filtering by quantitative profiles arXiv: Information Retrieval. ,(2012)
Hans-Peter Kriegel, Martin Ester, Jörg Sander, Xiaowei Xu, A density-based algorithm for discovering clusters in large spatial Databases with Noise knowledge discovery and data mining. pp. 226- 231 ,(1996)
Marcin Gorawski, Rafal Malczok, AEC Algorithm: A Heuristic Approach to Calculating Density-Based Clustering Eps Parameter Advances in Information Systems. pp. 90- 99 ,(2006) , 10.1007/11890393_10
John S. Whissell, Charles L. A. Clarke, Clustering for semi-supervised spam filtering Proceedings of the 8th Annual Collaboration, Electronic messaging, Anti-Abuse and Spam Conference on - CEAS '11. pp. 125- 134 ,(2011) , 10.1145/2030376.2030391
Hans‐Peter Kriegel, Peer Kröger, Jörg Sander, Arthur Zimek, Density‐based clustering Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery. ,vol. 1, pp. 231- 240 ,(2011) , 10.1002/WIDM.30