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Collaborative course selection recommendation method based on scores and teachers

A recommendation method and teacher's technology, applied in data processing applications, electronic digital data processing, digital data information retrieval, etc., can solve problems such as incompatibility, lack of comparability, and difficulty in obtaining historical information, and achieve reasonable models and vector training. reasonable effect

Inactive Publication Date: 2021-05-18
TIANJIN UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The key to this method is how to find the similar relationship between users. For newly enrolled students, it is relatively difficult to obtain historical information and lacks comparability, so it is not suitable for the scenario of course recommendation.

Method used

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  • Collaborative course selection recommendation method based on scores and teachers
  • Collaborative course selection recommendation method based on scores and teachers
  • Collaborative course selection recommendation method based on scores and teachers

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Embodiment Construction

[0036] Based on the traditional collaborative filtering algorithm and the principle of word2vec, the present invention proposes a course selection recommendation method for cooperative scores and teachers, emphatically introducing two features of scores and teachers. Substantive features of the present invention are as follows:

[0037](1) Calculate the similarity relationship between courses based on the principle of word2vec. Word2vec is a tool that Google open sourced in 2013 to represent words as vectors, and map the similarity between words through the cosine angle between vectors. In the present invention, all courses selected by each graduate are sorted in time series as an input text, and each course is regarded as a word. Due to the coherence between courses, each text can be regarded as a time series. Using the idea of ​​CBOW model to predict the central word through the context, the current course vector can be predicted according to the previous and subsequent co...

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Abstract

The invention relates to a collaborative course selection recommendation method based on scores and teachers, comprising the following steps: selecting all courses of graduates, teachers corresponding to the courses, and achievement information, and arranging them in chronological order as input data; For the statistical frequency of teachers, two Huffman trees are constructed to determine the Huffman code of each course and its teacher; random initialization of all model parameters, course vectors and teacher vectors; iteration; between course vectors The closer the distance is, the greater the similarity between the two courses is. When a freshman chooses a course he is interested in, he will recommend other courses related to it, considering the connection between courses and the students' interest in the course. teacher preferences.

Description

technical field [0001] The invention belongs to the technical field of recommendation based on collaborative filtering, and in particular relates to a collaborative course selection recommendation method based on scores and teachers. Background technique [0002] With the diversification of education development, designing a complete, scientific and reasonable curriculum system according to the subject characteristics of students' majors has become the focus of education that major universities are paying more and more attention to. At present, the curriculum arrangement of major universities mostly adopts the way that students choose courses freely. Although designated professional courses are divided according to different grades, the coherence and cohesion between courses of different grades are determined by students themselves. When students choose courses, they usually face the problem of not knowing which courses are suitable for them and which teachers are suitable f...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/9535G06Q50/20
CPCG06Q50/205G06F16/9535
Inventor 金志刚韩玥罗咏梅
Owner TIANJIN UNIV