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ADL
2000
Springer
265views Digital Library» more  ADL 2000»
13 years 9 months ago
Clustering and Identifying Temporal Trends in Document Databases
We introduce a simple and efficient method for clustering and identifying temporal trends in hyper-linked document databases. Our method can scale to large datasets because it ex...
Alexandrin Popescul, Gary William Flake, Steve Law...
CORR
2008
Springer
113views Education» more  CORR 2008»
13 years 5 months ago
Document stream clustering: experimenting an incremental algorithm and AR-based tools for highlighting dynamic trends
We address here two major challenges presented by dynamic data mining: 1) the stability challenge: we have implemented a rigorous incremental density-based clustering algorithm, i...
Alain Lelu, Martine Cadot, Pascal Cuxac
INCDM
2010
Springer
193views Data Mining» more  INCDM 2010»
13 years 9 months ago
Trend Mining in Social Networks: A Study Using a Large Cattle Movement Database
This paper reports on a mechanism to identify temporal spatial trends in social networks. The trends of interest are defined in terms of the occurrence frequency of time stamped p...
Puteri N. E. Nohuddin, Rob Christley, Frans Coenen...
KDD
1997
ACM
120views Data Mining» more  KDD 1997»
13 years 9 months ago
Discovering Trends in Text Databases
We describe a system we developed for identifying trends in text documents collected over a period of time. Trends can be used, for example, to discover that a company is shifting...
Brian Lent, Rakesh Agrawal, Ramakrishnan Srikant
KDD
2008
ACM
232views Data Mining» more  KDD 2008»
14 years 5 months ago
Anticipating annotations and emerging trends in biomedical literature
The BioJournalMonitor is a decision support system for the analysis of trends and topics in the biomedical literature. Its main goal is to identify potential diagnostic and therap...
Bernd Wachmann, Dmitriy Fradkin, Fabian Mörch...