Intelligent Approval of Access Control Flow in Office Automation Systems via Relational Modeling
Summary: arXiv:2604.11040v1 Announce Type: new
Abstract: Office automation (OA) systems play a crucial role in enterprise operations and management, with access control flow approval (ACFA) being a key component that manages the accessibility of various resources. However, traditional ACFA requires approval from the person in charge at each step, which consumes a significant amount of manpower and time. Its intelligence is a crucial issue that needs to be addressed urgently by all companies.
In this paper, we propose a novel relational modeling-driven intelligent approval (RMIA) framework to automate ACFA. Specifically, our RMIA consists of two core modules:
- Binary Relation Modeling Module: This module aims to characterize the coupling relation between applicants and approvers. It provides reliable basic information for ACFA decision-making from a coarse-grained perspective.
- Ternary Relation Modeling Module: Utilizing specific resource information as its core, this module characterizes the complex relations between applicants, resources, and approvers. It provides fine-grained gain information for informed decision-making.
The RMIA effectively fuses these two kinds of information to form the final decision. Extensive experiments have been conducted on two product datasets and an online A/B test to verify the effectiveness of the RMIA framework.
Introduction
In today’s fast-paced business environment, companies are increasingly reliant on office automation systems to streamline operations and enhance productivity. One of the most critical aspects of these systems is the Access Control Flow Approval (ACFA), which determines who can access specific resources at various stages of the workflow. However, the traditional approach to ACFA is often cumbersome, requiring manual approvals that can lead to delays and inefficiencies.
The Need for Intelligent Systems
As organizations grow, the volume of requests for access control increases significantly. This necessitates a more intelligent approach to managing approvals in OA systems. The lack of automation in traditional ACFA not only consumes valuable manpower but also opens up the risk of human error and bottlenecks in the decision-making process. Addressing these issues is essential for organizations seeking to enhance operational efficiency.
Overview of the RMIA Framework
The proposed RMIA framework is designed to automate the ACFA process by leveraging relational modeling techniques. By integrating both binary and ternary relation modeling, the framework offers a comprehensive view of the relationships between applicants, resources, and approvers.
Key Components of RMIA
- Binary Relation Modeling: This foundational module captures the basic relationship dynamics, allowing for initial evaluations of access requests based on applicant-approver relationships.
- Ternary Relation Modeling: This advanced module enriches the decision-making process by considering the specific resources involved, thus enabling a more nuanced understanding of access requirements.
Results and Conclusion
The results from the conducted experiments demonstrate that the RMIA framework significantly improves the efficiency and accuracy of the ACFA process. By automating the approval flow, organizations can reduce approval times and minimize manual intervention, ultimately leading to a more streamlined workflow.
In conclusion, the RMIA framework presents a promising solution for enhancing access control in office automation systems, addressing the urgent need for intelligent approval processes in modern enterprises.