Learning to rank only using training data from related domain

• Main Authors: GAO, Wei, CAI, Peng, WONG, Kam-Fai, ZHOU, Aoying
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2010
• Subjects: Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/4597; https://ink.library.smu.edu.sg/context/sis_research/article/5600/viewcontent/p162_gao.pdf
• Institution: Singapore Management University

Like traditional supervised and semi-supervised algorithms, learning to rank for information retrieval requires document annotations provided by domain experts. It is costly to annotate training data for different search domains and tasks. We propose to exploit training data annotated for a related...