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» Learning in Multi-Agent Systems
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SIGIR
2009
ACM
16 years 1 months ago
Reciprocal rank fusion outperforms condorcet and individual rank learning methods
Reciprocal Rank Fusion (RRF), a simple method for combining the document rankings from multiple IR systems, consistently yields better results than any individual system, and bett...
Gordon V. Cormack, Charles L. A. Clarke, Stefan B&...
ICFCA
2005
Springer
16 years 11 days ago
Lessons Learned in Applying Formal Concept Analysis to Reverse Engineering
A key difficulty in the maintenance and evolution of complex software systems is to recognize and understand the implicit dependencies that define contracts that must be respecte...
Gabriela Arévalo, Stéphane Ducasse, ...
WORDS
2003
IEEE
16 years 3 days ago
Using Co-ordinated Atomic Actions for Building Complex Web Applications: A Learning Experience
This paper discusses some of the typical characteristics of modern Web applications and analyses some of the problems the developers of such systems have to face. One of such type...
Avelino F. Zorzo, Panayiotis Periorellis, Alexande...
SG
2010
Springer
15 years 12 months ago
Art 101: Learning to Draw through Sketch Recognition
iCanDraw is a drawing tool that can assist novice users to draw. The goal behind the system is to enable the users to perceive objects beyond what they know and improve their spati...
Tracy Hammond, Manoj Prasad, Daniel Dixon
IJCNN
2000
IEEE
15 years 11 months ago
Unsupervised Learning of Neural Network Ensembles for Image Classification
In the field of pattern recognition, the combination of an ensemble of neural networks has been proposed as an approach to the development of high performance image classification...
Giorgio Giacinto, Fabio Roli, Giorgio Fumera