Analyze the Association between Attributes and Ratings Based on Data-driven Analysis Algorithms
- Resource Type
- Conference
- Authors
- Lai, Xiaochen; Zou, Jixie; Yang, Jialiu; Tong, Lu
- Source
- 2023 International Conference on Intelligent Media, Big Data and Knowledge Mining (IMBDKM) IMBDKM Intelligent Media, Big Data and Knowledge Mining (IMBDKM), 2023 International Conference on. :76-83 Mar, 2023
- Subject
- Computing and Processing
Education
Media
Filtering algorithms
Big Data
Information filters
Object recognition
Data mining
information gain
Apriori algorithm
Rating
objective attribute
- Language
Rating is an important indicator of users satisfaction with a product, and each product usually receives ratings from different groups and different perspectives. The analysis of the information contained in the rating will help to make improvements to the product. The purpose of this paper is to investigate the influence of objective attributes on user ratings, so as to identify the advantages and disadvantages of these objective attributes. This paper uses the Apriori algorithm to analyze the association between objective attribute values and their ratings, and uses information gain as the weight of the ratings to distinguish the objective attributes that have a greater impact on each ratings. The results of the experiments and analyses demonstrated that the method was effective in selecting four objective attributes among 134 objective attributes that were deeply related to ratings.