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SIGIR
2010
ACM
14 years 1 months ago
Learning more powerful test statistics for click-based retrieval evaluation
Interleaving experiments are an attractive methodology for evaluating retrieval functions through implicit feedback. Designed as a blind and unbiased test for eliciting a preferen...
Yisong Yue, Yue Gao, Olivier Chapelle, Ya Zhang, T...
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
14 years 10 months ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims
GECCO
2006
Springer
253views Optimization» more  GECCO 2006»
14 years 1 months ago
A novel approach to optimize clone refactoring activity
Achieving a high quality and cost-effective tests is a major concern for software buyers and sellers. Using tools and integrating techniques to carry out low cost testing are chal...
Salah Bouktif, Giuliano Antoniol, Ettore Merlo, Ma...
GECCO
2006
Springer
130views Optimization» more  GECCO 2006»
14 years 1 months ago
Pairwise sequence comparison for fitness evaluation in evolutionary structural software testing
Evolutionary algorithms are among the metaheuristic search methods that have been applied to the structural test data generation problem. Fitness evaluation methods play an import...
H. Turgut Uyar, A. Sima Etaner-Uyar, A. Emre Harma...
ICFEM
2009
Springer
14 years 4 months ago
Implementing and Applying the Stocks-Carrington Framework for Model-Based Testing
In this paper we describe the functional features and the architecture of a tool implementing the Stocks-Carrington framework (TTF) for model based testing (MBT). The resulting pro...
Maximiliano Cristiá, Pablo Rodríguez...