使用意见挖掘检测在线产品的有偏见的用户产品评级

IF 2.1 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Journal of Intelligent Systems Pub Date : 2023-01-01 DOI:10.1515/jisys-2022-9030

A. Chopra, V. S. Dixit

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引用次数: 0

摘要

摘要协同过滤推荐系统(CFRS)在当今的电子商务行业中起着至关重要的作用。cfrs收集用户的评分，并预测目标产品的推荐。通常，CFRS使用用户-产品评级来提出建议。通常这些用户-产品评级是有偏见的。较高的额定值被称为推力额定值(pr)，较低的额定值被称为核额定值(nr)。pr和nr是由人为用户注入的，目的是加重或降低产品的推荐。因此，有必要调查pr或nr并丢弃它们。在这项工作中，将意见挖掘方法应用于用户对产品给出的文本评论中，以检测pr和nr。该研究还通过评估精确度、召回率、f值和准确性等各种指标，考察了pr和nr对CFRS性能的影响。

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Detecting biased user-product ratings for online products using opinion mining

Abstract Collaborative filtering recommender system (CFRS) plays a vital role in today’s e-commerce industry. CFRSs collect ratings from the users and predict recommendations for the targeted product. Conventionally, CFRS uses the user-product ratings to make recommendations. Often these user-product ratings are biased. The higher ratings are called push ratings (PRs) and the lower ratings are called nuke ratings (NRs). PRs and NRs are injected by factitious users with an intention either to aggravate or degrade the recommendations of a product. Hence, it is necessary to investigate PRs or NRs and discard them. In this work, opinion mining approach is applied on textual reviews that are given by users for a product to detect the PRs and NRs. The work also examines the effect of PRs and NRs on the performance of CFRS by evaluating various measures such as precision, recall, F-measure and accuracy.

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来源期刊

Journal of Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

CiteScore

5.90

自引率

3.30%

发文量

审稿时长

51 weeks

期刊介绍： The Journal of Intelligent Systems aims to provide research and review papers, as well as Brief Communications at an interdisciplinary level, with the field of intelligent systems providing the focal point. This field includes areas like artificial intelligence, models and computational theories of human cognition, perception and motivation; brain models, artificial neural nets and neural computing. It covers contributions from the social, human and computer sciences to the analysis and application of information technology.