Designing visual text analysis methods to support sensemaking and modeling

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Abstract/Contents

Abstract
This dissertation examines the co-design of interactive visualizations and statistical analysis algorithms to improve the process of visual analytics--to create effective workflows where human cognition and algorithms work in tandem to yield insights about large and complex data. I present the results of applying a human-centered iterative design process to a variety of projects: visualization of statistical topic models, analysis tools to assess topic model quality and domain relevance, and descriptive phrases for text summarization. This work develops novel interactive visualizations, enables more efficient analytic workflows, and contributes to our understanding of human categorization, topic modeling, and text summarization. I also distill design principles and processes to help practitioners incorporate increasingly sophisticated models into data analysis tools. Across these projects, I demonstrate how we can effectively integrate diverse perspectives from information visualization, human-computer interaction, and machine learning to support effective model-driven data analysis.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2013
Issuance monographic
Language English

Creators/Contributors

Associated with Chuang, Jason Chia-Chen
Associated with Stanford University, Department of Computer Science.
Primary advisor Heer, Jeffrey Michael
Thesis advisor Heer, Jeffrey Michael
Thesis advisor Manning, Christopher D
Thesis advisor McFarland, Daniel
Advisor Manning, Christopher D
Advisor McFarland, Daniel

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Jason Chia-Chen Chuang.
Note Submitted to the Department of Computer Science.
Thesis Ph.D. Stanford University 2013
Location electronic resource

Access conditions

Copyright
© 2013 by Jason Chia-Chen Chuang
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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