A. Massaro, Palo Lisco, A. Lombardi, A. Galiano, Nicola Savino
{"title":"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","authors":"A. Massaro, Palo Lisco, A. Lombardi, A. Galiano, Nicola Savino","doi":"10.5121/IJAIA.2019.10103","DOIUrl":null,"url":null,"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.","PeriodicalId":93188,"journal":{"name":"International journal of artificial intelligence & applications","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.5121/IJAIA.2019.10103","citationCount":"10","resultStr":"{\"title\":\"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\",\"authors\":\"A. Massaro, Palo Lisco, A. Lombardi, A. Galiano, Nicola Savino\",\"doi\":\"10.5121/IJAIA.2019.10103\",\"DOIUrl\":null,\"url\":null,\"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. 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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
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.