Big Graphs & Machine Learning & Rich Interactions: the recipe for the future of search?
A Talk by Caroline Goulard
About this talk
In this presentation, I will discuss the idea that visualizing knowledge graphs can help uncover information that would otherwise remain unseen.
Network graphs are often rejected by non-technical users because of their visual complexity, sometimes for aesthetic but often indecipherable appearance.
However, I am convinced that they bring out new uses of information retrieval, to which we are not accustomed yet, but will perhaps prove to be more effective than our classic search engines in the future.
To fuel this discussion, I will present a case study of the Knowl tool, produced by Dataveyes, the studio I co-founded.
Knowl is a graph visualization tool that helps you find useful information and understand how content is organized when dealing with a very large corpus of research publications.
It aims to overcome the weaknesses of traditional search engines (like Google Scholar), when looking for something you don’t know how to formulate.
For example, when looking for scenarios to work on the next anti-Covid vaccine.
How can graph visualization provide solutions to this Dark Knowledge problem?
This is the bet I would like to offer for your consideration.
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Categories covered by this talk
Human Data Interactions
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