Sensors Recommender
A data-to-AI system that deeply understands every single user’s behaviors in real-time and automatically recommend those products, information and services the customer get interested. That is the key to keep your customers delighted and activated, as well as improving CTR and other metrics you care.
Full-process Recommendation system of "Data + Intelligence + Feedback"
Sensors recommender system is a full-process close-loop recommendation scheme. It collects full-end data (involving App, Web, Applet, H5, server, business data, third party, etc.), and uses deep learning and semantic analysis model to form the recommendation engine, and the recommend results can be real-time analyzed and feedback, to realize accurate algorithm iteration.
The technical architecture of Sensors Recommender
Powerful algorithm function
Provide advanced machine learning algorithms such as deep learning to ensure excellent recommendation effect.
Private deployment
Enable private deployment, ensure data security, and enable secondary development of algorithm model.
Manual intervention
Provide a visual platform that can get the recommend results more fitting business real demands.
Real-time recommendation
Full-end data collecting, algorithm model calculating, and recommendation results showing are all in real time, to satisfy high effectiveness user experience.
“White box” algorithm
Provide overall solutions to enable your algorithm team. Enable secondary development of algorithm module, and you can call algorithm module and get results flexibly.
Accurate algorithm iteration
Based on outcome analysis, you can flexibly adjust the feature set, iterate the model parameters, and adjust the solution to meet business changes and get higher returns.
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