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WWW
2011
ACM
14 years 8 months ago
Characterizing search intent diversity into click models
Modeling a user’s click-through behavior in click logs is a challenging task due to the well-known position bias problem. Recent advances in click models have adopted the examin...
Botao Hu, Yuchen Zhang, Weizhu Chen, Gang Wang, Qi...
CIKM
2009
Springer
15 years 8 months ago
Post-rank reordering: resolving preference misalignments between search engines and end users
No search engine is perfect. A typical type of imperfection is the preference misalignment between search engines and end users, e.g., from time to time, web users skip higherrank...
Chao Liu, Mei Li, Yi-Min Wang
ISDA
2008
IEEE
15 years 8 months ago
Inertia-Adaptive Particle Swarm Optimizer for Improved Global Search
This paper describes a method for improving the final accuracy and the convergence speed of Particle Swarm Optimization (PSO) by adapting its inertia factor in the velocity updati...
Kaushik Suresh, Sayan Ghosh, Debarati Kundu, Abhir...
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
16 years 2 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
122
Voted
CVPR
2007
IEEE
16 years 3 months ago
A Variational Approach to the Evolution of Radial Basis Functions for Image Segmentation
In this paper we derive differential equations for evolving radial basis functions (RBFs) to solve segmentation problems. The differential equations result from applying variation...
Greg G. Slabaugh, Huong Quynh Dinh, Gozde B. Unal