A mouse-trajectory based model for predicting query-URL relevance

A mouse-trajectory based model for predicting query-URL relevance

For the learning-to-ranking algorithms used in commercial search engines, a conventional way to generate the training examples is to employ professional annotators to label the relevance of query-url pairs. Since label quality depends on the expertise of annotators to a large extent, this process is...

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Bibliographic Details
Main Authors: Song, Hengjie, Liao, Ruoxue, Zhang, Xiangliang, Yang, Qiang, Miao, Chun Yan
Other Authors: School of Computer Engineering
Format: Conference Paper
Language:English
Published: 2014
Subjects:
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Online Access:https://hdl.handle.net/10356/104498
http://hdl.handle.net/10220/18850
http://www.aaai.org/ocs/index.php/AAAI/AAAI12/paper/view/4968

Internet

https://hdl.handle.net/10356/104498
http://hdl.handle.net/10220/18850
http://www.aaai.org/ocs/index.php/AAAI/AAAI12/paper/view/4968

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