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机构地区:[1]复旦大学计算机科学技术学院上海数据科学重点实验室,上海200433
出 处:《小型微型计算机系统》2017年第4期664-670,共7页Journal of Chinese Computer Systems
基 金:国家自然科学基金项目(60873115)资助;教育部-中国移动科研基金项目(MCM20123011)资助;上海市科技发展基金项目(13dz2260200;13511504300)资助;国家"八六三"高技术研究发展计划项目(2012AA02A602)资助
摘 要:广泛且持久的业务运作造就了业务大数据背景,大量的业务运作历史记录信息可被利用,互联网时期企业唾手可得的运行日志和参考流程模型给当今企业流程建模带来了新的机遇.如何利用这些机遇尚缺乏有效的支撑技术,流程挖掘和流程检索仅可靠单一的来源、静态的标准、全局化粒度缓解上述矛盾,且不能体现流程设计这种活动创造性本质.提出一种用平均感知机综合历史执行日志和参考模型片段的设计时模型推荐方法.其特点是兼顾了日志数据和流程模型,并将设计这种人类所特有的创造性和对现实环境的适应性结合进流程建模过程中.在三个不同类型的数据集上的实验表明,本方法具有更好的人类行为贴近度:真实的生物信息学实验流程(实验准确度53.69%)、相关工作对比数据集(+42.35%)、Pro M仿真工具PLG生成的大规模数据(比只考虑流程时+9.46%,比只考虑日志时+5.94%),证实了通过抽取多重特征的平均感知机的流程设计时即时推荐技术可有效地辅助流程业务建模.Extensive and longtime business operations contribute to the business big data. In the Intemet ear, abundant business process models and executing logs become available, which could be reused in the practice of business process modeling. Considering the fact that limited sources, static criteria, and coarse granularity employed by traditional process mining and process retrieval, there still call for effective approaches to take the advantage of this opportunity in order to highlight the creative nature in business process modeling. To meet the requirement, we propose a novel recommendation approach in process design based on the average perceptron over multi- ple information sources. It is characterized by taking into account historical logs as well as available process models, and combine hu- man creativity and the adaptability to real situations at the stage of business process modeling. Experimental results against three differ- ent types of data demonstrate its excellence in simulating human behaviors. Specifically, promising performance are achieved to the real bioinformatics process data(53.69% ),related work data set (gain with + 42.35% ), and synthetic data set by ProM's PLG tool (gain with +9.46% by considering both case structure and log items,or +5.94% gaining in contrast to merely logs).
分 类 号:TP311[自动化与计算机技术—计算机软件与理论]
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