CS Seminar: Wenwen Dou

Event Date: 
Thu, 2014-02-27 09:30 - 10:45

Wenwen Dou

Dept. of Computer Science University of North Carolina Charlotte

Thursday, February 27, 2014 9:30AM-10:45AM
655 McBryde


The increasing amount of textual data bears valuable insights in domains including business intelligence and public policy. While automated text-analysis algorithms produce compelling results on summarizing and mining textual data, the end results are often too complex to for average users to make decisions upon. In this talk, I will introduce my research efforts on integrating automated data- analysis algorithms with visual analytics systems that help decision makers make sense of large-scale textual data interactively.

My research promotes topical trends and event structures as essential ingredients in depicting large text collections. Events, which are characterized by changes in topics, location, people, and time, are key elements for decision makers to understand, analyze, and even respond to certain activities (e.g. protests, crowd gatherings). I will introduce systems that integrate text-analysis algorithms with human assessment of the extracted topics and events. To scale up my approach, I will present an architecture that takes advantage of parallel processing and cloud computing methods to enable the collection and analysis of vast amount of textual data. To further incorporate existing knowledge into topic models, I will introduce new approaches that leverage keywords/tags to shape the formation of topics and events. Through integrating statistical methods, the scalable architecture, and interactive visualizations, we provide an analysis environment for uncovering hidden topics and events, and extracting valuable insights from text corpora.

Dr. Wenwen Dou is an assistant research professor in the department of Computer Science at the University of North Carolina at Charlotte. Her research interests include Visual Analytics, Text Mining, and Human Computer Interaction. In particular, her research lies at the intersection of interactive visualization and text mining, with the specific area referred to as Visual Text Analytics. She has conducted extensive research on interactive visual analysis of large text corpora, in particular with focus on temporal analysis and event extraction. Dou has worked with various analytics domains in reducing information overload and providing interactive visual means to analyzing unstructured information. She has experience in turning cutting-edge research into technologies that have broad societal impacts, partially demonstrated by supports from both academic and industry partners, including PNNL, US Army Research Office, US Special Operations Command, NSF, US Army Engineering Research and Development Center, and Lowe’s company Inc.