Interweaving Queries and Pattern Mining for Event Sequence Exploration

Faculty: 
Rahul Basole
Students: 
Po-Ming Law

Exploring event sequences by defining queries alone or by using mining algorithms alone is often not sufficient to support analysis. Analysts often interweave querying and mining in a recursive manner during event sequence analysis: sequences extracted as query results are used for mining patterns, patterns generated are incorporated into a new query for segmenting the sequences, and the resulting segments are mined or queried again. To support flexible analysis, we propose a framework that describes the process of interwoven querying and mining. Based on this framework, we developed MAQUI, a Mining And Querying User Interface that enables recursive event sequence exploration. Our case studies with marketing analysts and a health informatics professional showed the efficacy of MAQUI.

Lab: 
Director: 
Rahul C. Basole
Faculty: 
Rahul C. Basole
Students: 
Terrance Law, Tim Major, Arjun Srinivasan, Biswajyoti Pal, Tyler Labean

The Computational Enterprise Science Lab focuses on the design, analysis, and management of complex enterprise systems (e.g. organizations, supply chains, business ecosystems) using information visualization, modeling/simulation, and system science approaches.