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» Scaling Clustering Algorithms to Large Databases
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WWW
2007
ACM
14 years 9 months ago
Why we search: visualizing and predicting user behavior
The aggregation and comparison of behavioral patterns on the WWW represent a tremendous opportunity for understanding past behaviors and predicting future behaviors. In this paper...
Eytan Adar, Daniel S. Weld, Brian N. Bershad, Stev...
SIGCOMM
2000
ACM
14 years 10 hour ago
Memory-efficient state lookups with fast updates
Routers must do a best matching pre x lookup for every packet solutions for Gigabit speeds are well known. As Internet link speeds higher, we seek a scalable solution whose speed ...
Sandeep Sikka, George Varghese
ACL
1997
13 years 9 months ago
Deriving Verbal and Compositional Lexical Aspect for NLP Applications
Verbal and compositional lexical aspect provide the underlying temporal structure of events. Knowledge of lexical aspect, e.g., (a)telicity, is therefore required for interpreting...
Bonnie J. Dorr, Mari Broman Olsen
SCIENTOMETRICS
2010
158views more  SCIENTOMETRICS 2010»
13 years 6 months ago
Rete-netzwerk-red: analyzing and visualizing scholarly networks using the Network Workbench Tool
The enormous increase in digital scholarly data and computing power combined with recent advances in text mining, linguistics, network science, and scientometrics make it possible...
Katy Börner, Weixia Huang, Micah Linnemeier, ...
KDD
2009
ACM
188views Data Mining» more  KDD 2009»
14 years 9 months ago
Mining discrete patterns via binary matrix factorization
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Bao-Hong Shen, Shuiwang Ji, Jieping Ye