流程挖掘

  • 网络process mining
流程挖掘流程挖掘
  1. 在第一部分,文章给出了一种基于日志的新的流程挖掘算法,给出了算法的Java实现。

    In the first section , a new process mining algorithm based on logs is brought up , and the implement with java for the algorithm is given .

  2. 针对Q算法的不足,提出了基于日志的流程挖掘算法,实现对短循环和隐含任务的挖掘。

    Towards the deficiency of alpha algorithm , a new process mining algorithm based on logs is brought up , which can make application for the implicit task and short cycle task .

  3. 在详细讨论流程挖掘方法前,文章对与挖掘有关的技术和理论进行了描述,包括日志的数学表达模型,Petri网和工作流网的相关属性,Petri网到工作流网的映射关系等。

    Before discussing the mining method , the paper describes some technology and theory related to process mining , including algebra express of log and definition and property of Petri Net and Workflow Net , creating the mapping relationship between Petri Net and Workflow Net .

  4. 流程挖掘是为进一步流程优化提供知识规则;

    Process excavation aims to supporting knowledge and rules for process optimization .

  5. 流程挖掘在社会日常生产工作中起到非常重要的作用。

    Process mining plays a very important role in our daily production work .

  6. 基于流程挖掘的临床路径设计方法研究

    The Design of Clinical Pathway Based on Process Mining

  7. 流程挖掘是一种从实际业务执行日志中发现结构化流程信息的过程。

    Process mining is to discover structured process description from real execution data .

  8. 基于遗传方法的流程挖掘技术的研究

    Research on Process Mining Based on Genetic Algorithm

  9. 一种建模的新技术:流程挖掘

    Process Mining & A New Model Technology

  10. 其中分为两个部分:流程挖掘算法和流程挖掘算法的改进。

    It includes two sections : process mining algorithm and improvement of process mining algorithm .

  11. 因此,该算法在处理复杂且非结构化的流程挖掘方面具有明显优势。

    Therefore , the algorithm in dealing with complex and unstructured process mining has obvious advantages .

  12. 流程挖掘研究

    Study on Process Mining

  13. 当前的主要流程挖掘算法之所以大都不能完全发掘出这种结构,主要原因就是不能挖掘出非局部的非自由选择结构。

    The current main process mining algorithms can not discover the structure of it , mainly because they can not dig out the non-local non-free-choice construct .

  14. γ算法克服了目前流程挖掘的局限,不仅仅挖掘任务间的逻辑关系,同时可以挖掘流程的管理操作。

    These algorithms solve the current problems of process mining : not only mining the logical relationship between activities , but also mining the management operations of process .

  15. 流程挖掘的目的就是从日志数据中抽取信息构建商业流程执行时的模型,从而能跟踪改进流程。

    Process mining aims at extracting information from logs to build up business processes models as they are being executed , and use them to monitor and improve business processes .

  16. 结果表明,本文使用流程挖掘技术提出的临床路径集模型为医疗信息系统的临床路径挖掘设计和应用提供了一种有效的解决方案。

    The result shows that the clinical pathway set model proposed in this paper with process mining techniques provides an effective solution for clinical pathway mining measure and application in health information system .

  17. 该方法把工作流参与者的工作内容相似程度作为角色识别的标准,通过流程挖掘方法把相似度高的子流程识别为与角色对应的子流程,实现一种较为客观的角色识别方法。

    The similarity in the content of workflow participants is used as the measurement for role identification . Sub-process with high level of similarity is recognized as the process undertook by a certain role , thus a relatively objective role identification method is achieved .

  18. 在讨论了Web使用模式的挖掘流程及挖掘技术后,架构了一种Web使用模式挖掘工具。

    After discussing mining procedure and mining technology of Web operation mode , a mining tool for Web operation mode is constructed .

  19. 将城市文化转化为城市文化资本的具体流程是挖掘城市文化资源、寻找城市文化记忆和构建城市文化认同。

    The urban culture into urban culture of the specific process is the mining capital city culture resources , looking for urban culture and the construction of urban cultural identity memory .

  20. 每一个内部管理流程都是挖掘员工更大潜力的机会。

    Every built-in management process is an opportunity for unleashing more human potential .

  21. 介绍了数据挖掘技术的背景、概念、流程、数据挖掘算法,并阐述了数据挖掘技术的应用现状。

    This paper introduces the background , concept and process of data mining technology and data mining algorithms , and elaborates the application actuality of data mining technology .

  22. 提出的粗糙数据挖掘模型和挖掘算法操作方便、易于理解,降低了存储空间,提高了流程工业数据挖掘的运行效率。

    The proposed rough data mining model and data mining algorithm are understood easily and operating conveniently , can decrease the store space and improve the efficiency of process industrial data mining .

  23. 介绍了Web数据挖掘的概念、Web数据挖掘的流程、Web数据挖掘的分类以及3类Web数据挖掘的应用问题。

    This article introduces the concept of Web data mining , the flow of Web data mining , the classification of Web data mining and the application of three Web data mining .

  24. 在实际研究上,采用CRISP-DM商业挖掘流程标准,使用挖掘工具SPSSClementine对所在企业的会员销售数据进行研究。

    In the actual research , Using CRISP - DM commercial mining process standards and enterprises membership sales data were studied by using the tools of mining SPSS Clementine .

  25. 流程工业粒度数据挖掘技术研究与应用

    Studies on Granularity Data Mining and Its Application in Process Industry

  26. 本文以此为主要背景来研究流程工业粒度数据挖掘技术。

    In this paper the process industrial granularity data mining is mainly based on the ethylene cracking furnace system .

  27. 在进行用户需求分析中,需要以新技术的思路去分析传统流程,深层次挖掘用户需求,提出更为合理可行,更为优化的业务实现方案。

    When the users ' demands are analyzed , new technology mentality shall be used to analyze the traditional flow , excavate the users ' new demands and propose optimized service transformation plan which is more reasonable and feasible . 2 .

  28. 本算法亦可挖掘出选择,并行,及混合结构的流程模型。最后,我们用Java在Prom上实现了一个流程挖掘算法的插件,并通过挖掘一系列业务流程实例,得到业务流程图。

    The algorithm can also dig out the choice , parallel , and mixed structure of process models . Finally , we implement a process mining algorithm plug-in of the Prom buy using java , and get business process diagrams by digging a series of business process instances .

  29. 通过对评估中阈值的设定,有效的对流程进行筛选和分类,并且借助该评估方法可以评估流程改良效果,为后续流程挖掘工作提供决策依据。

    Process screening and classification , including excavation work for the follow-up by the threshold value setting can evaluate the process improvement and provide basis for decision making in further process mining work .

  30. 其次,从概念上提出了业务流程的多维数据模型,并提出了业务流程进行多维数据分析的维度和度量,从而可以为流程的多维数据挖掘提供一个前提。

    Secondly , the paper proposes the multidimensional data model of the business process in concept . At the same time , the paper proposes the dimensions and metrics of the business process for multidimensional data analysis .