CAMBRIDGE, Mass., Sept. 24, 2019 /PRNewswire/ -- Relativity6, Inc., a provider of artificial intelligence and machine learning predictive analytics, today announced that a paper authored by the company's data science team has been accepted for presentation at the 18th IEEE International Conference on Machine Learning and Applications (ICMLA 2019).
Relativity6's paper entitled "Maximizing Customer Lifetime Value using Stacked Neural Networks: An Insurance Industry Application" proposes a two-stage neural network architecture: Stage-I uses a self-attention mechanism and collaborative metric learning to generate product recommendations, and Stage-II uses a neural network-based survival analysis to infer insurance product recommendations that maximize customer lifetime. The full paper may be accessed here.
"Our team is very excited to participate in ICMLA 2019," said CTO Abraham Rodriguez . "Customer lifetime value is widely used as a key performance metric to evaluate retention strategies in insurance industry, but many retention products do not seek to maximize customer lifetime value by layering on additional patterns. We were keen to explore temporal patterns and excited about, not just total customer retention, but maximizing customer lifetime value on an individual basis."
ICMLA 2019 will be held in Boca Raton, Florida, on December 16-19, 2019. Its goal is to bring together researchers and practitioners to present the latest achievements and innovations in the area of machine learning.
At Relativity6, we're obsessed with the industry classification problem and Artificial Intelligence. And more so, we're obsessed with solving the industry classification problem with AI. To that end, we've developed an algorithm that delivers 80%+ accuracy when classifying businesses across the globe via API with responses in under 1 second. All you input is a business's name and address.
Every day we iterate on our algorithms, feed them more data, and find techniques and strategies to get more accurate.
Check out the video below to see the Relativity6 Industry Classification API in action: