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.

Pending Publication Date: 2021-05-25
上海阅想教育科技有限公司
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AI Technical Summary

Problems solved by technology

[0003] It is particularly difficult to choose suitable questions from the massive question bank in the market, and it is difficult to distinguish different teaching progress and students' learning conditions. How to recommend suitable practice questions to students with different learning conditions, learning progress and learning preferences, so as to improve students' learning efficiency Be the key to user experience

Method used

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  • Method for constructing recommendation system based on application data

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Embodiment Construction

[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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Abstract

The invention relates to the technical field of recommendation systems, in particular to a method for constructing a recommendation system based on application data, comprising a user feature model, a question feature model, a question recommendation engine, a structured data source and a model strategy, the question recommendation engine is composed of a business application layer, a recommendation system layer, a core data layer, an off-line calculation layer, a recommendation system background and a scheduling / coordination server, data are subjected to hierarchical processing, appropriate exercise questions are recommended according to different teaching schedules and student learning conditions, the learning schedules and learning preferences of students, and the learning efficiency of students is improved. According to the teaching progress, the learning condition of the student and the preference of the teacher, appropriate questions are recommended for the teacher to form the test paper, and the reliability and validity of the test paper are improved.

Description

technical field [0001] The invention relates to the technical field of recommendation systems, in particular to a method for building a recommendation system based on application data. Background technique [0002] It is particularly difficult to choose the right topic in the massive question bank. , thus, there is a growing need for a method for building recommender systems based on application data. [0003] It is particularly difficult to choose suitable questions from the massive question bank in the market, and it is difficult to distinguish different teaching progress and students' learning conditions. How to recommend suitable practice questions to students with different learning conditions, learning progress and learning preferences, so as to improve students' learning efficiency Be the key to user experience. In addition, according to the teaching progress, students' learning situation and teacher's preference, how to recommend appropriate questions for teachers ...

Claims

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Application Information

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IPC IPC(8): G06F16/9535G06F16/958G06Q50/20
CPCG06Q50/205G06F16/9535G06F16/958
Inventor 王莹莹王阳杨欢
Owner 上海阅想教育科技有限公司
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