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» Approximate data mining in very large relational data
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KDD
2005
ACM
140views Data Mining» more  KDD 2005»
16 years 4 months ago
Graphs over time: densification laws, shrinking diameters and possible explanations
How do real graphs evolve over time? What are "normal" growth patterns in social, technological, and information networks? Many studies have discovered patterns in stati...
Jure Leskovec, Jon M. Kleinberg, Christos Faloutso...
SDM
2004
SIAM
165views Data Mining» more  SDM 2004»
15 years 5 months ago
Visualizing RFM Segmentation
Segmentation based on RFM (Recency, Frequency, and Monetary) has been used for over 50 years by direct marketers to target a subset of their customers, save mailing costs, and imp...
Ron Kohavi, Rajesh Parekh
ECIR
2004
Springer
15 years 5 months ago
Performance Analysis of Distributed Architectures to Index One Terabyte of Text
We simulate different architectures of a distributed Information Retrieval system on a very large Web collection, in order to work out the optimal setting for a particular set of r...
Fidel Cacheda, Vassilis Plachouras, Iadh Ounis
CSCW
2000
ACM
15 years 8 months ago
Using Web annotations for asynchronous collaboration around documents
Digital web-accessible annotations are a compelling medium for personal comments and shared discussions around documents. Only recently supported by widely used products, “in-co...
Jonathan J. Cadiz, Anoop Gupta, Jonathan Grudin
136
Voted
WWW
2010
ACM
15 years 11 months ago
Large-scale bot detection for search engines
In this paper, we propose a semi-supervised learning approach for classifying program (bot) generated web search traffic from that of genuine human users. The work is motivated by...
Hongwen Kang, Kuansan Wang, David Soukal, Fritz Be...