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» Finding Groups in Data: Cluster Analysis with Ants
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KDD
2009
ACM
203views Data Mining» more  KDD 2009»
16 years 6 days ago
Characterizing individual communication patterns
The increasing availability of electronic communication data, such as that arising from e-mail exchange, presents social and information scientists with new possibilities for char...
R. Dean Malmgren, Jake M. Hofman, Luis A. N. Amara...
CGF
2010
189views more  CGF 2010»
14 years 11 months ago
Space-in-Time and Time-in-Space Self-Organizing Maps for Exploring Spatiotemporal Patterns
Spatiotemporal data pose serious challenges to analysts in geographic and other domains. Owing to the complexity of the geospatial and temporal components, this kind of data canno...
Gennady L. Andrienko, Natalia V. Andrienko, Sebast...
ESEM
2008
ACM
15 years 1 months ago
Phase distribution of software development effort
Effort distribution by phase or activity is an important but often overlooked aspect compared to other steps in the cost estimation process. Poor effort allocation is among the ma...
Ye Yang, Mei He, Mingshu Li, Qing Wang, Barry W. B...
BMCBI
2004
131views more  BMCBI 2004»
14 years 11 months ago
A web services choreography scenario for interoperating bioinformatics applications
Background: Very often genome-wide data analysis requires the interoperation of multiple databases and analytic tools. A large number of genome databases and bioinformatics applic...
Remko de Knikker, Youjun Guo, Jin-long Li, Albert ...
CINQ
2004
Springer
163views Database» more  CINQ 2004»
15 years 5 months ago
Frequent Itemset Discovery with SQL Using Universal Quantification
Algorithms for finding frequent itemsets fall into two broad classes: (1) algorithms that are based on non-trivial SQL statements to query and update a database, and (2) algorithms...
Ralf Rantzau