Document selection methodologies for efficient and effective learning-to-rank
Javed A. Aslam, Evangelos Kanoulas, Virgil Pavlu, Stefan Savev, Emine Yılmaz · 2009
Learning-to-rank has attracted great attention in the IR community. Much thought and research has been placed on query-document feature extraction and development of sophisticated learning-to-rank algorithms. However, relatively little research has been conducted on selecting documents for learning-to-rank data sets nor on the effect of these choices on the efficiency and effectiveness of learning-to-rank algorithms.