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交互式工作流数据分析的时间挖掘

Temporal mining for interactive workflow data analysis
课程网址: http://videolectures.net/kdd09_berlingerio_tmiwda/  
主讲教师: Michele Berlingerio
开课单位:
开课时间: 2009-09-14
课程语种: 英语
中文简介:
在过去几年里, 人们对流程日志的分析越来越感兴趣。几种建议的技术, 如工作流挖掘, 旨在自动派生基础工作流模型。但是, 当前的方法很少关注流程日志中包含的重要信息: 时间戳, 它用于定义执行任务的顺序顺序。在这项工作中, 我们试图通过在提取的知识中明确包含时间来克服这些限制, 从而使时间信息成为分析过程中的一流公民。这样就可以识别在连续任务之间以不同的转换时间执行的明显相同的过程执行。 本文提出了一个用户交互探索的框架, 即对给定过程中执行组的压缩表示。该框架基于对现有挖掘模式的使用: 时间注释序列 (tas)。它们旨在提取顺序模式, 其中两个事件之间的每个转换都用输入数据中出现的典型转换时间进行注释。与被提取的 tas, 代表可能的频繁执行的集合以他们的典型的转折时间, 一些因素化操作员被修造。这些运算符根据可能的平行或可能的相互排他执行压缩此类执行。最后, 这种压缩表示通过勘探图, 即时间注释图 (tag) 呈现给用户。允许用户, 域专家, 探索不同的和替代的分解对应于实际执行的不同解释。根据用户的选择, 系统放弃或保留了关于实际执行的某些假设, 并显示了实际数据的相应重新聚合所产生的结果。
课程简介: In the past few years there has been an increasing interest in the analysis of process logs. Several proposed techniques, such as workflow mining, are aimed at automatically deriving the underlying workflow models. However, current approaches only pay little attention on an important piece of information contained in process logs: the timestamps, which are used to define a sequential ordering of the performed tasks. In this work we try to overcome these limitations by explicitly including time in the extracted knowledge, thus making the temporal information a first-class citizen of the analysis process. This makes it possible to discern between apparently identical process executions that are performed with different transition times between consecutive tasks. This paper proposes a framework for the user-interactive exploration of a condensed representation of groups of executions of a given process. The framework is based on the use of an existing mining paradigm: Temporally-Annotated Sequences (TAS). These are aimed at extracting sequential patterns where each transition between two events is annotated with a typical transition time that emerges from input data. With the extracted TAS, which represent sets of possible frequent executions with their typical transition times, a few factorizing operators are built. These operators condense such executions according to possible parallel or possible mutual exclusive executions. Lastly, such condensed representation is rendered to the user via the exploration graph, namely the Temporally-Annotated Graph (TAG). The user, the domain expert, is allowed to explore the different and alternative factorizations corresponding to different interpretations of the actual executions. According to the user choices, the system discards or retains certain hypotheses on actual executions and shows the consequent scenarios resulting from the coresponding re-aggregation of the actual data.
关 键 词: 时间戳; 时间注释图; 交互式工作流数据
课程来源: 视频讲座网
最后编审: 2020-06-25:liush
阅读次数: 99