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» Results Merging Algorithm Using Multiple Regression Models
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SIGIR
2004
ACM
13 years 11 months ago
Learning to cluster web search results
Organizing Web search results into clusters facilitates users' quick browsing through search results. Traditional clustering techniques are inadequate since they don't g...
Hua-Jun Zeng, Qi-Cai He, Zheng Chen, Wei-Ying Ma, ...
IJCNN
2008
IEEE
14 years 5 days ago
Sparse kernel density estimator using orthogonal regression based on D-Optimality experimental design
— A novel sparse kernel density estimator is derived based on a regression approach, which selects a very small subset of significant kernels by means of the D-optimality experi...
Sheng Chen, Xia Hong, Chris J. Harris
CLEF
2005
Springer
13 years 11 months ago
CLEF 2005: Multilingual Retrieval by Combining Multiple Multilingual Ranked Lists
: We participated in two tasks: Multi-8 two-years-on retrieval and Multi-8 results merging. For our multi-8 two-years-on retrieval work, simple multilingual ranked lists are first ...
Luo Si, Jamie Callan
ESANN
2006
13 years 7 months ago
Using Regression Error Characteristic Curves for Model Selection in Ensembles of Neural Networks
Regression Error Characteristic (REC) analysis is a technique for evaluation and comparison of regression models that facilitates the visualization of the performance of many regre...
Aloísio Carlos de Pina, Gerson Zaverucha
SIGMOD
2007
ACM
181views Database» more  SIGMOD 2007»
14 years 5 months ago
Progressive and selective merge: computing top-k with ad-hoc ranking functions
The family of threshold algorithm (i.e., TA) has been widely studied for efficiently computing top-k queries. TA uses a sort-merge framework that assumes data lists are pre-sorted...
Dong Xin, Jiawei Han, Kevin Chen-Chuan Chang