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arXiv · 1905.13368

Fast Online "Next Best Offers" using Deep Learning

Rekha Singhal·Gautam Shroff·Mukund Kumar·Sharod Roy·Sanket Kadarkar·Rupinder virk·Siddharth Verma·Vartika Tiwari
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Abstract

In this paper, we present iPrescribe, a scalable low-latency architecture for recommending 'next-best-offers' in an online setting. The paper presents the design of iPrescribe and compares its performance for implementations using different real-time streaming technology stacks. iPrescribe uses an ensemble of deep learning and machine learning algorithms for prediction. We describe the scalable real-time streaming technology stack and optimized machine-learning implementations to achieve a 90th percentile recommendation latency of 38 milliseconds. Optimizations include a novel mechanism to deploy recurrent Long Short Term Memory (LSTM) deep learning networks efficiently.

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Rekha Singhal, Gautam Shroff, Mukund Kumar, Sharod Roy, Sanket Kadarkar, Rupinder virk, Siddharth Verma, Vartika Tiwari. 2019-05-31. Fast Online "Next Best Offers" using Deep Learning. https://arxiv.org/abs/1905.13368

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