Introduction
Bimonthly, started in 1957
Administrator
Shanxi Provincial Education Department
Sponsor
Taiyuan University of Technology
Publisher
Ed. Office of Journal of TYUT
Editor-in-Chief
SUN Hongbin
ISSN: 1007-9432
CN: 14-1220/N
Administrator
Shanxi Provincial Education Department
Sponsor
Taiyuan University of Technology
Publisher
Ed. Office of Journal of TYUT
Editor-in-Chief
SUN Hongbin
ISSN: 1007-9432
CN: 14-1220/N
location: home > paper >
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A Learning to Rank Method Based on Multi-layer Clonal Selection
DOI:
10.16355/j.cnki.issn1007-9432tyut.2018.05.016
Received:
Accepted:
| Corresponding author | Institute | |
| TIAN Yuling | College of Information and Computer, Taiyuan University of Technology |
abstract:
A learning to rank method based on multi-layer clonal selection is presented.The clonal selection theory is applied to learn ranking functions and an improvement is applied to the traditional clonal selection algorithm.A layered mutation method and a multi-layer clonal selection architecture are used to evolve antibody repertoire and get the optimal ranking function.Proposed method is evaluated on the LETOR data collection, and results show that the proposed algorithm is more effective than baseline algorithms in most cases.
Keywords:
clonal selection; learning to rank; ranking function;