Summarization of Multidimensional Process Traces for Analysis under Edit-distance Constraints

2020 IEEE International Conference on Services Computing (SCC)(2020)

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Motivation: Business processes and workflows exhibit data models in the form of multi-dimensional sequence of objects. As exemplified in Figure 1 , a business processes, represented as a directed acyclic graph of activities, generates execution traces as a sequence of activities with associated multi-dimensional attributes. For example, an activity in the loan application process can contain information about the person and the department that are responsible for the activity, the person who performs the activity, and the group to which she belongs. Businesses analyze operational data for insights such as understanding workflow patterns and bottlenecks [1] , verifying conformance to policies or regulations [2] , or revealing clusters of common behavior [3] .
edit distance (390), summary space (280), summarization scheme (220), process model (150), similarity search (140), contractive property (140), analysis task (120), trace clustering (120), attribute based summarization (110), distance threshold (100), business process (100), similarity search task (95), topic based summarization (95), positive rate (80), topic summarization (80), data item (80), reduced f summarization (79), multi dimensional attribute (79), distance constraint (70), multidimensional set (70), lithography dataset (70), conformance fitness (70), positive rate false positive rate (69), k topic summarization (63), similarity measure (60), sequential relationship (60), process trace (60), clustering result (60), loan application (56), structural complexity (50)
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