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Weijia Cai
Researcher at IBM
Publications - 3
Citations - 274
Weijia Cai is an academic researcher from IBM. The author has contributed to research in topics: Visualization & Visual analytics. The author has an hindex of 2, co-authored 3 publications receiving 246 citations.
Papers
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Journal ArticleDOI
TIARA: Interactive, Topic-Based Visual Text Summarization and Analysis
TL;DR: An enhanced, LDA-based topic analysis technique is introduced that automatically derives a set of topics to summarize a collection of documents and their content evolution over time and an effective visual metaphor is developed to transform abstract and often complex text summarization results into a comprehensible visual representation.
Proceedings ArticleDOI
Interactive, topic-based visual text summarization and analysis
TL;DR: This paper presents the design and development of a time-based, visual text summary that effectively conveys complex text summarization results produced by the Latent Dirichlet Allocation (LDA) model and describes a set of rich interaction tools that allow users to work with a createdVisual text summary to further interpret the summarizationresults in context and examine the text collection from multiple perspectives.
Book ChapterDOI
COBRA --- A Visualization Solution to Monitor and Analyze Consumer Generated Medias
TL;DR: COBRA (COrporate Brand and Reputation Analysis) is described, a visual analytics solution that surfaces the text mining and statistical analysis capabilities described in earlier COBRA papers.