The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
웹 2.0의 맥락에서 자원을 공유하고 소비하는 과정에서 사용자와 자원 간의 상호작용이 점점 더 빈번해지고 있습니다. 그러나 현재 자원 가격 책정에 관한 연구는 주로 자원 자체의 속성에 초점을 맞추고 있으며, 자원 공유 참여자의 이익을 고려하지 않습니다. 이러한 문제를 해결하기 위해 본 논문에서는 다중 에이전트 게임 이론을 기반으로 한 자원-사용자 상호 작용 평가의 가격 책정 메커니즘을 설정합니다. 또한, 사용자 유사성, 링크 분석에 따른 평가 편향, 학계 부정 행위 처벌 등도 모델에 포함됩니다. 181명의 학자 데이터와 Wanfang 데이터베이스의 509개 기사를 기반으로 본 논문은 5483개월 동안 13개의 가격 책정 실험을 수행했으며 결과는 이 모델이 다른 가격 책정 모델보다 더 효과적이라는 것을 보여줍니다. 즉, 자원 자원의 가격 책정 정확도는 94.2%입니다. 사용자가치평가의 정확도는 96.4%이다. 게다가 이 모델은 사용자와 리소스 내의 관계를 직관적으로 보여줄 수 있습니다. 사례 연구는 또한 사용자의 지식 수준이 자신의 권위와 긍정적인 상관 관계가 없다는 것을 보여줍니다. 학계 부정행위를 적발하고 처벌하는 것은 연구자와 자원을 객관적으로 평가하는 데 도움이 됩니다. 본 논문에서 제안하는 과학기술 자원과 이용자의 가격 책정 메커니즘은 과학기술 자원의 공정한 거래를 전제로 한다.
Fanying ZHENG
Zhejiang University
Fu GU
Zhejiang University
Yangjian JI
Zhejiang University
Jianfeng GUO
Chinese Academy of Sciences,University of Chinese Academy of Sciences
Xinjian GU
Zhejiang University
Jin ZHANG
Zhejiang University
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부
Fanying ZHENG, Fu GU, Yangjian JI, Jianfeng GUO, Xinjian GU, Jin ZHANG, "Consumption Pricing Mechanism of Scientific and Technological Resources Based on Multi-Agent Game Theory: An Interactive Analytical Model and Experimental Validation" in IEICE TRANSACTIONS on Information,
vol. E104-D, no. 8, pp. 1292-1301, August 2021, doi: 10.1587/transinf.2020BDP0020.
Abstract: In the context of Web 2.0, the interaction between users and resources is more and more frequent in the process of resource sharing and consumption. However, the current research on resource pricing mainly focuses on the attributes of the resource itself, and does not weigh the interests of the resource sharing participants. In order to deal with these problems, the pricing mechanism of resource-user interaction evaluation based on multi-agent game theory is established in this paper. Moreover, the user similarity, the evaluation bias based on link analysis and punishment of academic group cheating are also included in the model. Based on the data of 181 scholars and 509 articles from the Wanfang database, this paper conducts 5483 pricing experiments for 13 months, and the results show that this model is more effective than other pricing models - the pricing accuracy of resource resources is 94.2%, and the accuracy of user value evaluation is 96.4%. Besides, this model can intuitively show the relationship within users and within resources. The case study also exhibits that the user's knowledge level is not positively correlated with his or her authority. Discovering and punishing academic group cheating is conducive to objectively evaluating researchers and resources. The pricing mechanism of scientific and technological resources and the users proposed in this paper is the premise of fair trade of scientific and technological resources.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2020BDP0020/_p
부
@ARTICLE{e104-d_8_1292,
author={Fanying ZHENG, Fu GU, Yangjian JI, Jianfeng GUO, Xinjian GU, Jin ZHANG, },
journal={IEICE TRANSACTIONS on Information},
title={Consumption Pricing Mechanism of Scientific and Technological Resources Based on Multi-Agent Game Theory: An Interactive Analytical Model and Experimental Validation},
year={2021},
volume={E104-D},
number={8},
pages={1292-1301},
abstract={In the context of Web 2.0, the interaction between users and resources is more and more frequent in the process of resource sharing and consumption. However, the current research on resource pricing mainly focuses on the attributes of the resource itself, and does not weigh the interests of the resource sharing participants. In order to deal with these problems, the pricing mechanism of resource-user interaction evaluation based on multi-agent game theory is established in this paper. Moreover, the user similarity, the evaluation bias based on link analysis and punishment of academic group cheating are also included in the model. Based on the data of 181 scholars and 509 articles from the Wanfang database, this paper conducts 5483 pricing experiments for 13 months, and the results show that this model is more effective than other pricing models - the pricing accuracy of resource resources is 94.2%, and the accuracy of user value evaluation is 96.4%. Besides, this model can intuitively show the relationship within users and within resources. The case study also exhibits that the user's knowledge level is not positively correlated with his or her authority. Discovering and punishing academic group cheating is conducive to objectively evaluating researchers and resources. The pricing mechanism of scientific and technological resources and the users proposed in this paper is the premise of fair trade of scientific and technological resources.},
keywords={},
doi={10.1587/transinf.2020BDP0020},
ISSN={1745-1361},
month={August},}
부
TY - JOUR
TI - Consumption Pricing Mechanism of Scientific and Technological Resources Based on Multi-Agent Game Theory: An Interactive Analytical Model and Experimental Validation
T2 - IEICE TRANSACTIONS on Information
SP - 1292
EP - 1301
AU - Fanying ZHENG
AU - Fu GU
AU - Yangjian JI
AU - Jianfeng GUO
AU - Xinjian GU
AU - Jin ZHANG
PY - 2021
DO - 10.1587/transinf.2020BDP0020
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E104-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2021
AB - In the context of Web 2.0, the interaction between users and resources is more and more frequent in the process of resource sharing and consumption. However, the current research on resource pricing mainly focuses on the attributes of the resource itself, and does not weigh the interests of the resource sharing participants. In order to deal with these problems, the pricing mechanism of resource-user interaction evaluation based on multi-agent game theory is established in this paper. Moreover, the user similarity, the evaluation bias based on link analysis and punishment of academic group cheating are also included in the model. Based on the data of 181 scholars and 509 articles from the Wanfang database, this paper conducts 5483 pricing experiments for 13 months, and the results show that this model is more effective than other pricing models - the pricing accuracy of resource resources is 94.2%, and the accuracy of user value evaluation is 96.4%. Besides, this model can intuitively show the relationship within users and within resources. The case study also exhibits that the user's knowledge level is not positively correlated with his or her authority. Discovering and punishing academic group cheating is conducive to objectively evaluating researchers and resources. The pricing mechanism of scientific and technological resources and the users proposed in this paper is the premise of fair trade of scientific and technological resources.
ER -