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PMS-Sorting: A New Sorting Algorithm Based on Similarity

Hongbin Wang1, Lianke Zhou1, Guodong Zhao1,*, Nianbin Wang1, Jianguo Sun1, Yue Zheng2, Lei Chen3

College of Computer Science and Technology, Harbin Engineering University, Harbin, 150001, China.
Liren College of Yanshan University, Yanshan University, Qinhuangdao, 066004, China.
College of Engineering and Computing, Georgia Southern University, Georgia, 30458, USA.

* Corresponding Author: Guodong Zhao. Email: email.

Computers, Materials & Continua 2019, 59(1), 229-237. https://doi.org/10.32604/cmc.2019.04628

Abstract

Borda sorting algorithm is a kind of improvement algorithm based on weighted position sorting algorithm, it is mainly suitable for the high duplication of search results, for the independent search results, the effect is not very good and the computing method of relative score in Borda sorting algorithm is according to the rule of the linear regressive, but position relationship cannot fully represent the correlation changes. aimed at this drawback, the new sorting algorithm is proposed in this paper, named PMS-Sorting algorithm, firstly the position score of the returned results is standardized processing, and the similarity retrieval word string with the query results is combined into the algorithm, the similarity calculation method is also improved, through the experiment, the improved algorithm is superior to traditional sorting algorithm.

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Cite This Article

APA Style
Wang, H., Zhou, L., Zhao, G., Wang, N., Sun, J. et al. (2019). Pms-sorting: A new sorting algorithm based on similarity. Computers, Materials & Continua, 59(1), 229-237. https://doi.org/10.32604/cmc.2019.04628
Vancouver Style
Wang H, Zhou L, Zhao G, Wang N, Sun J, Zheng Y, et al. Pms-sorting: A new sorting algorithm based on similarity. Comput Mater Contin. 2019;59(1):229-237 https://doi.org/10.32604/cmc.2019.04628
IEEE Style
H. Wang et al., “PMS-Sorting: A New Sorting Algorithm Based on Similarity,” Comput. Mater. Contin., vol. 59, no. 1, pp. 229-237, 2019. https://doi.org/10.32604/cmc.2019.04628



cc Copyright © 2019 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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