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Web of Proceedings - Francis Academic Press
Web of Proceedings - Francis Academic Press

Design and Implementation of Personalized Learning Platform Based on Big Data

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DOI: 10.25236/isetbm.2019.055

Author(s)

Xueming Bai

Corresponding Author

Xueming Bai

Abstract

The paper designs and implements a personalized learning platform for search. Based on big data technology, users search keywords on the platform which excavates and filters information from the huge cloud resources and pushes it to users. Through the mining of related web data, valuable information such as users' behavior, habits, preferences, etc. can be provided. The platform then integrates and reverses relevant recommendations for users to achieve private determination. The crawler system uses the scrapy crawler framework, the search engine service uses the Elasticsearch framework, and the data collection engine runs in the following environment: cloud server, scrapyd official deployment tool, and scrapydweb visual crawler monitoring framework. The website platform is based on the Python Django framework development. The project is based on uWSGI and Nginx as the production environment for the project, and built on the Docker container's service environment. The effect of the system is to realize the learning of artificial intelligence.

Keywords

Personalized learning; Knowledge graph; Search engine; Big data