Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 12
3667-3672

Collaborative filtering recommendation algorithm based on single-valued neutrosophic set

Li Penga,b
Su Xinjieb
Bai Shizhenb
a. Postdoctoral Mobile Station of Business Administration, b. School of Management, Harbin University of Commerce, Harbin 150028, China
DOI: 10.19734/j.issn.1001-3695.2021.06.0199

Abstract

User fuzzy evaluation in recommendation system usually cause low recommendation accuracy, in order to alleviate the problem, this paper designed a collaborative filtering recommendation model based on single-valued neutrosophic set. Firstly, this paper constructed a user-item scoring matrix, divided user rating, and converted the user rating according to the single-valued neutrosophic set calculation formula in order to obtain the true value membership degree, uncertain value membership degree and non-true value membership degree respectively. Next, this paper introduced the calculation formula of extreme evaluation as the penalty coefficient of extreme rating, based on which the similarity calculation formula is designed according to the single-valued neutrosophic set score. Finally, this model obtained the final-user similarity by combining the Jaccard correlation coefficient. The proposed collaborative filtering recommendation method was compared with the traditional similarity recommendation methods on the public data set MovieLens. The experimental results show that the proposed method is improved about 2-3 percent in index of RMSE and MAE, and the recommendation accuracy is efficiently promoted to deal with the fuzzy problem.

Foundation Support

黑龙江省自然科学基金项目(LH2019F043)
哈尔滨商业大学青年科研项目(2019DS012)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.06.0199
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 12
Section: Algorithm Research & Explore
Pages: 3667-3672
Serial Number: 1001-3695(2021)12-025-3667-06

Publish History

[2021-12-05] Printed Article

Cite This Article

李鹏, 苏忻洁, 白世贞. 基于单值中智集的协同过滤推荐算法 [J]. 计算机应用研究, 2021, 38 (12): 3667-3672. (Li Peng, Su Xinjie, Bai Shizhen. Collaborative filtering recommendation algorithm based on single-valued neutrosophic set [J]. Application Research of Computers, 2021, 38 (12): 3667-3672. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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