Hello everybody, my name is Xiaoyu Zhang. I'm from the University of California, Davis
Today I'll present our ontology-based knowledge visualization system---ConceptScope.
When we get a new research article, legal document or transcript of technical panel discussions to read,
a common question we like to ask is "What is this document about?"
We want to know the answer to this question as soon as possible.
And sometimes we even want to know "What is this document about in a specific domain?"
And furthermore, "What if there are more than one document to read?"
So our solution to answer these questions is to take use of a hierarchical knowledge storage model called ontology,
and combine it with the Bubble Treemap visualization as well as some coordinated views
to create this interactive knowledge visualization tool.
Our tool provides two visualization modes.
First, let's start from the exploratory mode.
Here is the visualization we see just now.
We can zoom in closer to check the area we are interested in and the information about the concepts.
In this visualization, the colored circle in the middle represents a concept appearing both in the document and in the ontology.
And the nested contours around it show its parents concept.
The more inside the contour is, the deeper its corresponding concept is in the ontology,
which also means the more specific the concept is.
If we further zoom in to a specific concept, for example "svm",
we can also check the wordcloud of related concepts in the document about "svm".
We embed this visualization in our ConceptScope system with multiple coordinated views.
Users can scroll over the concept list to browse all the concepts and their occurrence frequency in the document.
If they find the concept they are interested in, they can follow the highlights to locate them in the Bubble Treemap,
and further inspect the concordance view,
or hover over the transcript view to check the original sentences.
Now let's move on to the comparison mode.
We can open multiple documents in the system at the same time.
For example, here we compare the transcripts of three TED talks about computer science.
By hovering over the bubbles and check the coordinated highlighting,
we can find the common and unique computer-science-related concepts across the three documents
Again, we can turn to the concept list to get an overview of all the concepts appearing here.
And from the sparkline behind a concept,
we can find the relative appearance frequency of the same concept across the three documents.
We conducted a remote between-subject user study,
and compare our system with the widely accepted document visualization tool, Docuburst.
According to our user study, we find that our ConceptScope is good at visualizing domain-specific documents.
While Docuburst is better at visualizing the cross-disciplinary documents.
A second discovery is that our system is more suitable for users to explore their unfamiliar documents.
While Docuburst is more suitable for in-depth exploration of familiar documents.
To wrap up my presentation today, we try to answer the question that
"What is this document, or multiple documents, about in a specific domain?"
To answer this question, we take use of ontology and Bubble Treemap visualization,
as well as multiple coordinated views to create this prototype system called ConceptScope.
According to our between-subject the user study,
we find that our tool is especially useful for visualizing domain-specific and unfamiliar documents for users.
The source code of our system is available here at Github.
Finally, I would like to thank all the people who helped us with our project,
the participants of our user study, the reviewers of this paper,
last but not least, the sponsors of this project.
That ends my presentation today.
Thank you for listening and I'm ready to take questions