Parallel Learning to Rank for Information Retrieval

• Main Authors: WANG, Shuaiqiang, GAO, Byron J., WANG, Ke, LAUW, Hady W.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2011
• Subjects: learning to rank; mapreduce; parallel algorithms; information retrieval; cooperative coevolution; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/1517; https://ink.library.smu.edu.sg/context/sis_research/article/2516/viewcontent/sigir11.pdf
• Institution: Singapore Management University

Learning to rank represents a category of effective ranking methods for information retrieval. While the primary concern of existing research has been accuracy, learning efficiency is becoming an important issue due to the unprecedented availability of large-scale training data and the need for cont...