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» Evaluating algorithms that learn from data streams
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150
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SDM
2009
SIAM
223views Data Mining» more  SDM 2009»
16 years 1 months ago
Context Aware Trace Clustering: Towards Improving Process Mining Results.
Process Mining refers to the extraction of process models from event logs. Real-life processes tend to be less structured and more flexible. Traditional process mining algorithms...
R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aa...
IPPS
2005
IEEE
15 years 10 months ago
Practical Divisible Load Scheduling on Grid Platforms with APST-DV
Divisible load applications consist of a load, that is input data and associated computation, that can be divided arbitrarily into independent pieces. Such applications arise in m...
Krijn van der Raadt, Yang Yang, Henri Casanova
179
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SPIRE
2005
Springer
15 years 10 months ago
Using the k-Nearest Neighbor Graph for Proximity Searching in Metric Spaces
Proximity searching consists in retrieving from a database, objects that are close to a query. For this type of searching problem, the most general model is the metric space, where...
Rodrigo Paredes, Edgar Chávez
PODS
1999
ACM
133views Database» more  PODS 1999»
15 years 9 months ago
Processing and Optimization of Multiway Spatial Joins Using R-Trees
One of the most important types of query processing in spatial databases and geographic information systems is the spatial join, an operation that selects, from two relations, all...
Dimitris Papadias, Nikos Mamoulis, Yannis Theodori...
ECCV
2010
Springer
15 years 8 months ago
Bundle Adjustment in the Large
Abstract. We present the design and implementation of a new inexact Newton type algorithm for solving large-scale bundle adjustment problems with tens of thousands of images. We ex...