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The purpose of this study is to investigate how book group recommendations can be used as a meaningful way to suggest suitable books to users, given the increasing number of individuals engaging in sharing and discussing books on the web.

The authors propose reviews fine-grained classification (CFGC) and its related models such as CFGC1 for book group recommendation. These models can categorize reviews successively by function and role. Constructing the BERT-BiLSTM model to classify the reviews by function. The frequency characteristics of the reviews are mined by word frequency analysis, and the relationship between reviews and total book score is mined by correlation analysis. Then, the reviews are classified into three roles: celebrity, general and passerby. Finally, the authors can form user groups, mine group features and combine group features with book fine-grained ratings to make book group recommendations.

Overall, the best recommendations are made by Synopsis comments, with the accuracy, recall, F-value and Hellinger distance of 52.9%, 60.0%, 56.3% and 0.163, respectively. The F1 index of the recommendations based on the author and the writing comments is improved by 2.5% and 0.4%, respectively, compared to the Synopsis comments.

Previous studies on book recommendation often recommend relevant books for users by mining the similarity between books, so the set of book recommendations recommended to users, especially to groups, always focuses on the few types. The proposed method can effectively ensure the diversity of recommendations by mining users’ tendency to different review attributes of books and recommending books for the groups. In addition, this study also investigates which types of reviews should be used to make book recommendations when targeting groups with specific tendencies.

Internal audit executives instruct the internal audit department to supervise corporate business management activities, evaluate internal controls and risks and provide recommendations for operating. Therefore, this paper aims to confirm whether and how the supervisory ability of the chief internal audit executive enhances the internal audit department’s function to prevent corporate fraud. Based on the results, this paper further researches the role of the supervisory board position in this relationship.

This paper examines 922 small and medium-sized listed enterprises in China from 2010 to 2017 and empirically investigates the influence of the internal audit executive’s supervisory ability (IAESA) on the occurrence of corporate fraud.

The results reveal that the IAESA is significantly negatively correlated with the occurrence of corporate fraud. This suppression effect is more pronounced when the internal audit executive is also the company’s supervisor. However, if the internal audit executive is the chairman of the board of supervisors, the suppression effect no longer exists. This paper therefore confirms that the IAESA curbs corporate fraud via the improvement of the internal corporate control level.

Because the sample data was limited by the information disclosure level of the included companies, the sample size was relatively small as compared with those of other studies.

This study not only expands the research perspective in the field of internal audit functions but also provides a decision-making reference for the prevention of corporate fraud.

This paper extends an approach that might be able to curb corporate fraud.

A comprehensive index was developed using data envelope analysis to quantify the supervisory ability of internal audit executives. Based on this, this research confirms that the internal audit department performs a “firewall function” to prevent corporate fraud.