Interactive Event Sequence Prediction for Marketing Analysts, CHI 2020 (Late Breaking Works)
Fan Du, Shunan Guo, Sana Malik, Eunyee Koh, Sungchul Kim, and Zhicheng Liu
Data-Driven Multi-level Segmentation of Image Editing Logs, CHI 2020
Zipeng Liu, Zhicheng Liu, and Tamara Munzner
MAQUI: Interweaving Queries and Pattern Mining for Recursive Event Sequence Exploration, VIS 2018
Po-Ming Law, Zhicheng Liu, Sana Malik, and Rahul C. Basole
CoreFlow: Extracting and Visualizing Branching Patterns from Event Sequences, EuroVis 2017
Zhicheng Liu, Bernard Kerr, Mira Dontcheva, Justin Grover, Matthew Hoffman, Alan Wilson
Mining, Pruning and Visualizing Frequent Patterns for Temporal Event Sequence Analysis, Event Event Workshop 2016
Zhicheng Liu, Himel Dev, Mira Dontcheva and Matthew Hoffman
Patterns and Sequences: Interactive Exploration of Clickstreams to Understand Common Visitor Paths, VIS 2016
Zhicheng Liu, Yang Wang, Mira Dontcheva, Matthew Hoffman, Seth Walker and Alan Wilson
The collection and analysis of event sequence data occurs in many domains. For instance, e-commerce companies seek to understand customer behaviors from clickstream data and inform marketing decisions. User logs generated from desktop applications can be helpful to understand user intent and tasks for building intelligent assistants. In the healthcare domain, electronic health records are sources of information that can provide insights into whether recommended guidelines are followed. The sheer volume and complexity of event sequences present many challenges in the visual analysis of such data.
We employ and integrate methods such as data mining, visualization and predictive analytics to support visual analysis of event sequence data.