Dynamic Multi-Role Recommendation System for Personalized Experiences
Overview
The platform provides two different quizzes for “Explore the world” experiences and “stay at home” experiences. The Uzephra recommendation system recommends the best experiences for the user based on their choice to travel out or have fun staying at home. The inputs provided by the user during the quiz determine the experiences being suggested. In such a multi-role recommendation system, each experience’s data consists of the complete itinerary based on the geo-location and nature of the experience.
Technical Stack
Industry
Travel & Hospitality
Region
USA
Project Size
Non- Disclosable
Challenges & Solutions
The client wanted the usage of DynamoDB and deployment on AWS to keep the deployment cost minimum and only pay per use with the help of Serverless technique in collaboration with AWS Lambda functions.
- Solution: Our smart developers reconfigured the file structure and methods of the recommendation algorithm. Also, the development team suggested that we deploy the backend code on the AWS EC2 instance using a server-based approach instead of a serverless approach.
We used the Decimal package to handle integer data among the APIs and Database efficiently. Decimal is the numeric data type in DynamoDB, but it is not supported as a primary data type in Python.
- Solution: Finally, we created the necessary APIs to implement the recommendation algorithm using the data transmitted from the frontend and returned the required result with all the mandatory data fetched from DynamoDB.
AWS Lambda and Serverless could not handle the complex execution of recommendation algorithms.
- Solution: Our developers implemented the integration of the recommendation algorithms on priority as it was the most valuable feature of the project.
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Years of Business
Experience
Happy
Customers
Countries with
Happy Customers
Agile enabled
employees
Core Features
- Dashboard with an animated map
- Take Quiz for travel or stay at home option
- “Explore the world” quiz
- Recommendations based on quiz results
No. of Developer
01
Time Frame
June 2020-Ongoing
Experience With Bacancy
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