Already have graph data in a Neo4j instance? Here is how you can
apply LynxKite graph data science magic on it!
A major mobile wallet in Singapore faced challenges to sustain the
performance of its customer acquisition campaign. Using LynxKite,
data scientists of Lynx Analytics developed a graph-based marketing
methodology that identified communities and influencers and created a
more personalized and effective campaign.
We show how graph-metric-based targeted intervention can have a huge impact on
the course of an epidemic. We are using a simulation on a graph model of
a hypothetical infectious disease.
LynxKite provides hundreds of built-in operations from
computing the degree of nodes
to finding a coloring of the graph
and making predictions with a neural network.
But what to do if there is no built-in box for what you want?
LynxKite has many different options for you to use your custom formulas and code.
In this post I review all of them and explain why I would choose one over the other in
Between January and April 2020, a LynxKite team (Gabor, Marton and Fai) worked
with a group of undergraduate students, Victoria Teo, Ann Qi Neo, Jian Lai Ng
and Benita Neo, from The National University of Singapore (NUS) on their
Capstone Project. The project requires the students to complete a real-world
business analytics project based on the principles they learned from various
modules in their business analytics program.
I love reading about how software designs evolve. Finding the best way to represent and
communicate things is challenging both in the code and on the user-interface.
This article is my recollection of the journey that took us to LynxKite’s current design.
Given a map of a town (a graph, of course!), prospective customers and network access
points LynxKite helps us figuring out an optimal fiber network layout.
How can we use Gource and LynxKite to visualize the LynxKite Git commit history in different ways?
[...] Six years and
almost 16,000 commits
later, today we are extremely proud and excited to announce putting this tool
in the hands of the broader
community. We are confident that LynxKite can be an important tool in the hands
of data scientists around the world and it will help boost the adoption of often
neglected graph methods.