III-Core-Small: Collaborative Research: Mining and Optimizing Ad Hoc Workflows

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Ad hoc workflows are everywhere in service industry, scientific research, as well as daily life, such as workflows of customer service, trouble shooting, information search, etc. Optimizing ad hoc workflows thus has significant benefits to the society. Currently the execution of ad hoc workflows is based on human decisions, where misinterpretation, inexperience, and ineffective processing are not uncommon, leading to operation inefficiency. The goal of this research project is to design and develop fundamental models, concepts, and algorithms to mine and optimize ad hoc workflows. The project includes novel research on the following key areas: (1) Network Modeling and Structure Mining. A network model is built that statistically captures the execution characteristics of ad hoc workflows, and is optimized to improve the execution of new workflows with respect to different optimization objectives. (2) Workflow Artifact Mining. The network model built on workflow executions is then extended with workflow artifact mining to realize an optimization system that is able to take advantage of both executions and text contents. (3) Role Discovery and Relation Assessment. A computational framework is built to analyze the roles and relationships of agents involved in ad hoc workflow executions in order to further optimize workflows. Advances from this project include models to represent ad hoc workflows, algorithms for mining hidden collaborative models, and techniques that optimize ad hoc workflow processing. The project bridges two emerging research areas: service science and network science, and enriches the principles and technologies of data mining. It also enhances research infrastructure through the collaboration of team members from different areas (data mining, database, and network). This research is tightly integrated with education through student mentoring and curriculum development. Publications, software and course materials that arise from this project will be disseminated on the project website: URL: http://www.cs.ucsb.edu/~xyan/smartflow.htm