Training query filtering for semi-supervised learning to rank with pseudo labels

Transductive active learning – A new semi-supervised learning approach based on iteratively refined generative models to capture structure in data

(2015) Tobias Reitmaier et al.   INFORMATION SCIENCES

Learning to expand queries using entities

(2014) Wladmir C. Brandão et al.   Journal of the Association for Information Science and Technology

Learning to rank using smoothing methods for language modeling

(2013) Yuan Lin et al.   JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY

Combining active learning and semi-supervised learning to construct SVM classifier

(2013) Yan Leng et al.   KNOWLEDGE-BASED SYSTEMS

A unified framework for semi-supervised PU learning

(2013) Haoji Hu et al.   WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS

How useful is social feedback for learning to rank YouTube videos?

(2013) Sergiu Chelaru et al.   WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS

An effective approach to tweets opinion retrieval

(2013) Zhunchen Luo et al.   WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS

Predicting Query Performance by Query-Drift Estimation

(2012) Anna Shtok et al.   ACM TRANSACTIONS ON INFORMATION SYSTEMS

High performance query expansion using adaptive co-training

(2012) Jimmy Xiangji Huang et al.   INFORMATION PROCESSING & MANAGEMENT

SocialSearch  + : enriching social network with web evidences

(2012) Gae-won You et al.   WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS

Selecting optimal training data for learning to rank

(2011) Xiubo Geng et al.   INFORMATION PROCESSING & MANAGEMENT

A noise-tolerant graphical model for ranking

(2011) Xiubo Geng et al.   INFORMATION PROCESSING & MANAGEMENT

Opinion helpfulness prediction in the presence of “words of few mouths”

(2011) Richong Zhang et al.   WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS

Identifying mislabeled training data with the aid of unlabeled data

(2010) Donghai Guan et al.   APPLIED INTELLIGENCE

Active learning and semi-supervised learning for speech recognition: A unified framework using the global entropy reduction maximization criterion

(2009) Dong Yu et al.   COMPUTER SPEECH AND LANGUAGE

LETOR: A benchmark collection for research on learning to rank for information retrieval

(2009) Tao Qin et al.   Information Retrieval Journal

Semi-supervised document retrieval

(2008) Ming Li et al.   INFORMATION PROCESSING & MANAGEMENT

Semi-supervised and active learning with the probabilistic RBF classifier

(2008) Constantinos Constantinopoulos et al.   NEUROCOMPUTING

Logistic regression model for prediction of roof fall risks in bord and pillar workings in coal mines: An approach

(2008) Sanjay Kumar Palei et al.   SAFETY SCIENCE