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» Machine learning for online query relaxation
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KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 5 months ago
Machine learning for online query relaxation
In this paper we provide a fast, data-driven solution to the failing query problem: given a query that returns an empty answer, how can one relax the query's constraints so t...
Ion Muslea
TREC
2007
13 years 6 months ago
Relaxed Online SVMs in the TREC Spam Filtering Track
Relaxed Online Support Vector Machines (ROSVMs) have recently been proposed as an efficient methodology for attaining an approximate SVM solution for streaming data such as the on...
David Sculley, Gabriel Wachman
SIGIR
2012
ACM
11 years 7 months ago
Learning to suggest: a machine learning framework for ranking query suggestions
We consider the task of suggesting related queries to users after they issue their initial query to a web search engine. We propose a machine learning approach to learn the probab...
Umut Ozertem, Olivier Chapelle, Pinar Donmez, Emre...
ICDM
2009
IEEE
160views Data Mining» more  ICDM 2009»
13 years 11 months ago
Fast Online Training of Ramp Loss Support Vector Machines
—A fast online algorithm OnlineSVMR for training Ramp-Loss Support Vector Machines (SVMR s) is proposed. It finds the optimal SVMR for t+1 training examples using SVMR built on t...
Zhuang Wang, Slobodan Vucetic
ICML
2004
IEEE
13 years 10 months ago
Online learning of conditionally I.I.D. data
In this work we consider the task of relaxing the i.i.d assumption in online pattern recognition (or classification), aiming to make existing learning algorithms applicable to a ...
Daniil Ryabko