A Case Study of Research Improvements in an Service Industry Upgrading the Knowledge Base of the Information System and the Process Management: Data Flow Automation, Association Rules and Data Mining

A. Massaro, Palo Lisco, A. Lombardi, A. Galiano, Nicola Savino
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引用次数: 10

Abstract

In this paper is analyzed a case study of an upgrade of an industry communication system developed by following ‘Frascati’ research guidelines. The goal of the proposed model is to enhance the industry knowledge Base –KB- by acting directly on information communication system improvements and data system integration, enabling automated process and data processing. The paper follow all the steps performed during the project development: the preliminary data infrastructure design, the information infrastructure improvements, and data processing. Data processing is performed by a calculus engine embedding data mining association rules and Artificial Neural Network –ANN- predictive algorithms thus improving the research. The calculus engine has been implemented by a multiple variables model where the contract data are preliminary processed in order to define functions classifying the operation processes and activating automatically the service process management. The business intelligence –BI- operations are performed mainly by the calculus engine optimizing industry performances. The goal of the paper is to show how research and development –R&D- can be applied by gaining and optimizing the knowledge and processes of an Italian industry working in car services. The project has been developed with the collaboration of the industry ACI Global working in roadside assistance services. By means of a research project resources, the information technology –IT- infrastructure has been improved by new solutions of the communication system and of the data transfer. The proposed case of study provides a model and a guideline to follow in order to apply research in industry acting directly on data and information network.
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服务业研究改进:信息系统知识库升级与流程管理:数据流自动化、关联规则与数据挖掘
本文分析了一个遵循“弗拉斯卡蒂”研究准则开发的工业通信系统升级的案例研究。提出的模型的目标是通过直接作用于信息通信系统改进和数据系统集成,实现自动化过程和数据处理,来增强行业知识库(kb)。本文跟踪了项目开发过程中的所有步骤:初步的数据基础设施设计、信息基础设施改进和数据处理。数据处理由嵌入数据挖掘关联规则和人工神经网络(ann)预测算法的微积分引擎完成,从而提高了研究水平。演算引擎采用多变量模型实现,其中对合同数据进行初步处理,以定义对操作流程进行分类和自动激活业务流程管理的功能。商业智能(bi)操作主要由优化行业性能的微积分引擎来完成。本文的目标是展示如何通过获取和优化意大利汽车服务行业的知识和流程来应用研究和开发。该项目是与从事路边援助服务的ACI Global业界合作开发的。通过一个研究项目资源,通过通信系统和数据传输的新解决方案,改进了信息技术it基础设施。本文提出的研究案例为将研究应用于直接作用于数据和信息网络的行业提供了一个模型和指导方针。
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