Qing Liu, K. Taylor, Xiang Zhao, G. Squire, Xuemin Lin, C. Kloppers, Richard Miller
{"title":"CTrace: semantic comparison of multi-granularity process traces","authors":"Qing Liu, K. Taylor, Xiang Zhao, G. Squire, Xuemin Lin, C. Kloppers, Richard Miller","doi":"10.1145/2463676.2465268","DOIUrl":null,"url":null,"abstract":"A process trace describes the processes taken in a workflow to generate a particular result. Given many process traces, each with a large amount of very low level information, it is a challenge to make process traces meaningful to different users. It is more challenging to compare two complex process traces generated by heterogenous systems and have different levels of granularity. We present CTrace, a system that (1) lets users explore the conceptual abstraction of large process traces with different levels of granularity, and (2) provides semantic comparison among traces in which both the structural and the semantic similarity are considered. The above functions are underpinned by a novel notion of multi-granularity process trace and efficient multi-granularity similarity comparison algorithms.","PeriodicalId":87344,"journal":{"name":"Proceedings. ACM-SIGMOD International Conference on Management of Data","volume":"8 1","pages":"1121-1124"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. ACM-SIGMOD International Conference on Management of Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2463676.2465268","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A process trace describes the processes taken in a workflow to generate a particular result. Given many process traces, each with a large amount of very low level information, it is a challenge to make process traces meaningful to different users. It is more challenging to compare two complex process traces generated by heterogenous systems and have different levels of granularity. We present CTrace, a system that (1) lets users explore the conceptual abstraction of large process traces with different levels of granularity, and (2) provides semantic comparison among traces in which both the structural and the semantic similarity are considered. The above functions are underpinned by a novel notion of multi-granularity process trace and efficient multi-granularity similarity comparison algorithms.