Method and system for recommending content of online course forum based on text similarity

A text similarity and content recommendation technology, which is applied in special data processing applications, instruments, electronic digital data processing, etc., can solve the problem of less browsing behavior of students, achieve unified efficiency and effect, improve utilization rate, and reduce interference

Inactive Publication Date: 2018-12-21
BEIHANG UNIV
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  • Claims
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AI Technical Summary

Problems solved by technology

The collaborative filtering algorithm based on user similarity needs more user behaviors to calculate user similarity, but in online courses, some students may have very little browsing behavior, which makes it impossible to accurately recommend to them

Method used

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  • Method and system for recommending content of online course forum based on text similarity
  • Method and system for recommending content of online course forum based on text similarity
  • Method and system for recommending content of online course forum based on text similarity

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Embodiment Construction

[0030] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0031] The key implementation steps of the online course forum content recommendation method based on text similarity of the present invention are described below.

[0032] Step 1: Segment the text content of the discussion posts into words, and use the text similarity measurement method to identify similar discussion posts. After word segmentation, domain keywords of discussion posts are extracted.

[0033] Before calculating the text similarity, word vectors need to be extracted from the text content. The extraction process generally includes the following:

[0034] (1) Word segmentation, which is to divide long texts into words, which are the smallest interpretation units of language.

[0035] (2) Text model, which is to ...

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Abstract

The invention provides an online course forum content recommendation method and system based on text similarity, which is applicable to the application field of online education. The system includes word segmentation module, word vector and domain keyword extraction module, domain corpus and similar post recommendation list generation module. This method will discuss the text content of the post for word segmentation, extraction of word vectors and domain keywords; Using Historical Discussion Posts to Construct Domain Corpus; Generate a list of similar posts from the corpus for the discussionposts the user is browsing. The invention improves the utilization rate of historical discussion content, Using text similarity analysis, It can compare the semantic similarity of the two discussion posts more accurately from the course content level, recommend more needed similar posts for students, and use Jaccard distance for preliminary screening in advance, and then use WMD distance measurement to discuss the similarity between the posts, which improves the efficiency of the recommendation system and reduces the computational load.

Description

technical field [0001] The invention belongs to the field of online education, and relates to a content recommendation method and system for an online course forum. Background technique [0002] A characteristic of online courses is the lack of guidance from teachers, so many online courses include a forum function, each round (semester) of the forum is independent of each other, students can ask questions and discuss in the forum. However, the forum functions provided by online courses are often relatively simple, lacking functions such as indexing and searching. When the activity of the forum is low, the content of the forum is insufficient to provide assistance to students; and when the activity of the forum reaches its peak, a large number of repeated and irrelevant discussions make it difficult for students to find what they really need. Therefore, introducing course history discussion posts into the current forum and recommending them can help improve the utilization ...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q50/20
CPCG06Q50/205
Inventor 万寒于乔野高小鹏刘康旭丁军
Owner BEIHANG UNIV
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