Application of Machine Learning for Online Reputation

doi:10.1007/s11633-020-1275-7

CORC > 自动化研究所 > 中国科学院自动化研究所 > 学术期刊 > International Journal of Automation and Computing

	Application of Machine Learning for Online Reputation
	Ahmad Alqwadri 2; Mohammad Azzeh 1; Fadi Almasalha 2
刊名	International Journal of Automation and Computing
	2021
卷号	18 期号:3 页码:492-502
关键词	Reputation system rating aggregation machine learning consumer reliability user trust
ISSN号	1476-8186
DOI	10.1007/s11633-020-1275-7
英文摘要	Users on the Internet usually require venues to provide better purchasing recommendations. This can be provided by a reputation system that processes ratings to provide recommendations. The rating aggregation process is a main part of reputation systems to produce global opinions about the product quality. Naive methods that are frequently used do not consider consumer profiles in their calculations and cannot discover unfair ratings and trends emerging in new ratings. Other sophisticated rating aggregation methods that use a weighted average technique focus on one or a few aspects of consumers′ profile data. This paper proposes a new reputation system using machine learning to predict reliability of consumers from their profile. In particular, we construct a new consumer profile dataset by extracting a set of factors that have a great impact on consumer reliability, which serve as an input to machine learning algorithms. The predicted weight is then integrated with a weighted average method to compute product reputation score. The proposed model has been evaluated over three MovieLens benchmarking datasets, using 10-folds cross validation. Furthermore, the performance of the proposed model has been compared to previous published rating aggregation models. The obtained results were promising which suggest that the proposed approach could be a potential solution for reputation systems. The results of the comparison demonstrated the accuracy of our models. Finally, the proposed approach can be integrated with online recommendation systems to provide better purchasing recommendations and facilitate user experience on online shopping markets.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/44297]
专题	自动化研究所_学术期刊_International Journal of Automation and Computing
作者单位	1.Department of Software Engineering, Applied Science Private University, Amman 11931, Jordan 2.Department of Computer Science, Applied Science Private University, Amman 11931, Jordan
推荐引用方式 GB/T 7714	Ahmad Alqwadri,Mohammad Azzeh,Fadi Almasalha. Application of Machine Learning for Online Reputation[J]. International Journal of Automation and Computing,2021,18(3):492-502.
APA	Ahmad Alqwadri,Mohammad Azzeh,&Fadi Almasalha.(2021).Application of Machine Learning for Online Reputation.International Journal of Automation and Computing,18(3),492-502.
MLA	Ahmad Alqwadri,et al."Application of Machine Learning for Online Reputation".International Journal of Automation and Computing 18.3(2021):492-502.