This paper presents and describes an approach to generate innovative labeled datasets that enable automated text classifiers to automatically detect online employee reviews referring to accounting control deficiencies...This paper presents and describes an approach to generate innovative labeled datasets that enable automated text classifiers to automatically detect online employee reviews referring to accounting control deficiencies,facili-tating supplementary monitoring for auditors and management.Employees,who are on the front lines executing policies and procedures,play a critical role in a firm's control environment.Their feedback provides insights into how controls are functioning.Textual data were collected and manually coded using a structured coding scheme mapped to COSO internal control framework(2013)principles.The dataset is unique in that it provides a new source of data that has not been previously used in internal control research,offering new opportunities for exploring the relationship between employee feedback and control weaknesses,and shedding light on potential improvements in internal control practices.Downstream stakeholders(such as researchers,management,in-vestors,and auditors)can benefit by having rapid,automated means for filtering and prioritizing employee reviews for further investigation,with respect to accounting control issue mentions.展开更多
SaaS (Software-as-a-Service) is a service model provided by cloud computing. It has a high requirement for QoS (Quality of Software) due to its method of providing software service. However, manual identification and ...SaaS (Software-as-a-Service) is a service model provided by cloud computing. It has a high requirement for QoS (Quality of Software) due to its method of providing software service. However, manual identification and diagnosis for performance issues is typically expensive and laborious because of the complexity of the application software and the dynamic nature of the deployment environment. Recently, substantial research efforts have been devoted to automatically identifying and diagnosing performance issues of SaaS software. In this survey, we comprehensively review the different methods about automatically identifying and diagnosing performance issues of SaaS software. We divide them into three steps according to their function: performance log generation, performance issue identification and performance issue diagnosis. We then comprehensively review these methods by their development history. Meanwhile, we give our proposed solution for each step. Finally, the effectiveness of our proposed methods is shown by experiments.展开更多
文摘This paper presents and describes an approach to generate innovative labeled datasets that enable automated text classifiers to automatically detect online employee reviews referring to accounting control deficiencies,facili-tating supplementary monitoring for auditors and management.Employees,who are on the front lines executing policies and procedures,play a critical role in a firm's control environment.Their feedback provides insights into how controls are functioning.Textual data were collected and manually coded using a structured coding scheme mapped to COSO internal control framework(2013)principles.The dataset is unique in that it provides a new source of data that has not been previously used in internal control research,offering new opportunities for exploring the relationship between employee feedback and control weaknesses,and shedding light on potential improvements in internal control practices.Downstream stakeholders(such as researchers,management,in-vestors,and auditors)can benefit by having rapid,automated means for filtering and prioritizing employee reviews for further investigation,with respect to accounting control issue mentions.
基金supported by the National Key R&D Program of China(2022YFB3304300)the Humanities and Social Sciences Youth Foundation,Ministry of Education(23YJCZH221)the Natural Science Foundation of Shandong Province(ZR2023QE030).
文摘SaaS (Software-as-a-Service) is a service model provided by cloud computing. It has a high requirement for QoS (Quality of Software) due to its method of providing software service. However, manual identification and diagnosis for performance issues is typically expensive and laborious because of the complexity of the application software and the dynamic nature of the deployment environment. Recently, substantial research efforts have been devoted to automatically identifying and diagnosing performance issues of SaaS software. In this survey, we comprehensively review the different methods about automatically identifying and diagnosing performance issues of SaaS software. We divide them into three steps according to their function: performance log generation, performance issue identification and performance issue diagnosis. We then comprehensively review these methods by their development history. Meanwhile, we give our proposed solution for each step. Finally, the effectiveness of our proposed methods is shown by experiments.
