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An Improved LambdaMART Algorithm Based on the Matthew Effect
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-11-06
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Matthew effect is a desirable phenomenon for a ranking model in search engines and recommendation systems.
However, most of algorithms of learning to rank (LTR) do not pay attention to Matthew effect.
LambdaMART is a well-known LTR algorithm that can be further optimized based on Matthew effect.
Inspired by Matthew effect, we distinguish queries with different effectiveness and then assign a higher weight to a query with higher effectiveness.
We improve the gradient in the LambdaMART algorithm to optimize the queries with high effectiveness, that is, to highlight the Matthew effect of the produced ranking models.
In addition, we propose strategies of evaluating a ranking model and dynamically decreasing the learning rate to both strengthen the Matthew effect of ranking models and improve the effectiveness of ranking models.
We use Gini coefficient, mean-variance, quantity statistics, and winning number to measure the performances of the ranking models.
Experimental results on multiple benchmark datasets show that the ranking models produced by our improved LambdaMART algorithm can exhibit a stronger Matthew effect and achieve higher effectiveness compared to the original one and other state-of-the-art LTR algorithms.
American Psychological Association (APA)
Li, Jinzhong& Liu, Guanjun. 2018. An Improved LambdaMART Algorithm Based on the Matthew Effect. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1206637
Modern Language Association (MLA)
Li, Jinzhong& Liu, Guanjun. An Improved LambdaMART Algorithm Based on the Matthew Effect. Mathematical Problems in Engineering No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1206637
American Medical Association (AMA)
Li, Jinzhong& Liu, Guanjun. An Improved LambdaMART Algorithm Based on the Matthew Effect. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1206637
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1206637