Intelligent Approval of Access Control Flow in Office Automation Systems via Relational Modeling
Dugang Liu, Zulong Chen, Chuanfei Xu, Jiaxuan He, Yunlu Ma, Jia Xu

TL;DR
This paper introduces a relational modeling-driven framework to automate access control flow approval in office automation systems, reducing manual effort and improving decision accuracy.
Contribution
It presents a novel RMIA framework with binary and ternary relation modules for intelligent, automated access approval decision-making.
Findings
Effective in reducing approval time and manpower
Validated through experiments on product datasets and online A/B testing
Improves decision reliability in access control flow approval
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: (1) The binary relation modeling module aims to characterize the coupling relation between applicants and approvers and provide reliable basic information for ACFA decision-making from a coarse-grained perspective. (2) The ternary relation modeling module utilizes specific resource…
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