Method for constructing recommendation system based on application data
A recommendation system and application data technology, applied in the field of recommendation system, can solve the problems of difficulty in distinguishing teaching progress, students' learning situation, selection difficulties, etc., and achieve the effect of improving reliability and validity and improving learning efficiency.
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[0017] see figure 1 , the present invention provides a technical solution:
[0018] A method for building a recommendation system based on application data, comprising a user feature model, a topic feature model, a topic recommendation engine, a structured data source, and a model strategy. The topic recommendation engine consists of a business application layer 1, a recommendation system layer 2, and a core data Layer 3, offline computing layer 4, recommendation system background 5 and scheduling / coordination server 6.
[0019] The business application layer 1 includes questions, test paper centers, and exams / exercises. The recommendation system layer 2 is composed of sorting algorithms, filtering algorithms, AB shunting algorithms, and log collection algorithms. The core data layer 3 includes category-related data, topic correlation data, topic label data, high-quality question bank data, teacher preference data, student preference data, student learning situation data and ...
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