Jigsaw: Supporting Investigative Analysis through Interactive Visualization

By John T. Stasko, Carsten Görg, Zhicheng Liu. 2007 IEEE Symposium on Visual Analytics Science and Technology, 2007

662 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/4995fca834e5ab141f76c2d5e84b3b454e7b9d2e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

In Sociology and Political Science

Citations in the corpus

Word Cloud Explorer: Text Analytics Based on Word Clouds (2014, background): “The system consists of the central word cloud view and a number of other components providing additional information and functionality for the analysis.”
The Word Tree, an Interactive Visual Concordance (2008, neutral): “In addition, we are grateful to the users of Many Eyes for their creativity and willingness to provide feedback on an experimental visualization technique.”
Termite: visualization techniques for assessing textual topic models (2012, methodology): “In the following examples we use LDA models [21] with 25 to 50 topics, trained on abstracts from 372 IEEE InfoVis conference papers from 1995 to 2010 [23].”
Interpretation and trust: designing model-driven visualizations for text analysis (2012, background): “Example systems include FacetAtlas [11], Jigsaw [45] (a VAST’07 challenge winner), and Palantir [35] (a VAST’08 challenge winner).”
Interactive Visual Profiling of Musicians (2016, methodology): “Inspired by Jigsaw’s list view [48] and Parallel Tag Clouds [14], we designed an interface that allows for the exploration of various metadata information provided.”
Knowledge Generation Model for Visual Analytics (2014, methodology): “In the following we will demonstrate a detailed model application with Jigsaw [9, 39] and a comparative high level assessment of systems from different application domains.”
UTOPIAN: User-Driven Topic Modeling Based on Interactive Nonnegative Matrix Factorization (2013, methodology): “Another widely-used system, Jigsaw [33], provides various capabilities such as summarizing document cluster views and allows several basic interactions such as changing the number of clusters and initializing seed documents of clusters.”
Effects of Sensemaking Translucence on Distributed Collaborative Analysis (2016, background): “Other tools aim to help collaborators achieve common ground using collaborative visualizations [1, 8, 28, 31, 32, 46, 48].”