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Method for sub-surface retrieval of MOOC course based on ElasticSearch

A course and faceting technology, applied in the field of faceted retrieval of MOOC courses based on ElasticSearch, can solve problems such as single retrieval method, inability to meet more comprehensive needs of users, and insufficient intelligence of retrieval result output, so as to achieve the effect of improving accuracy

Inactive Publication Date: 2017-05-31
XI AN JIAOTONG UNIV
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AI Technical Summary

Problems solved by technology

[0005] The index content in the above method is not comprehensive enough, the retrieval method is single, and the retrieval result output is not intelligent enough
Therefore, this popular retrieval method cannot meet the more comprehensive needs of users

Method used

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  • Method for sub-surface retrieval of MOOC course based on ElasticSearch
  • Method for sub-surface retrieval of MOOC course based on ElasticSearch

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Embodiment Construction

[0034] The present invention will be further explained below in conjunction with specific embodiments and accompanying drawings.

[0035] The method for faceted retrieval of MOOC courses in the present invention realizes the retrieval of MOOC courses through faceted retrieval, including the following steps.

[0036] (1) Acquisition of metadata: First, obtain course metadata from the MOOC China resource service platform through the GET request specification based on the HTTP protocol, then parse the data and store the metadata in the local resource database;

[0037] (2) Index construction: first create an index in ElasticSearch through the Mapping file, and then use the batch import mechanism of ElasticSearch to index the MOOC course data in the local resource database in step (1) in the ElasticSearch cluster;

[0038] (3) Multi-field search and field weight setting: First, research and actually analyze the characteristics of MOOC course resources, and analyze the data of 7 fi...

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Abstract

The invention discloses a method for sub-surface retrieval of MOOC courses based on ElasticSearch. The technical scheme has the following steps of firstly acquiring the MOOC courses metadata, parsing and then storing; creating an index of the MOOC courses metadata in a ElasticSearch cluster; adding data of a plurality of fields to the fields to be retrieved, achieving the multi-field search, and setting different weights for the different fields; re-setting a plurality of sub-surfaces, screening and filtering the MOOC courses from the different sub-surfaces, and allowing users to create their own search path to achieve the sub-surface search, and setting a sort. The sorting according to the specific sub-face based on the MOOC courses search results makes the MOOC courses with the expected attributes as far as possible near the front, and the search results sort is completed; finally, a search service interface is set up, the MOOC courses retrieval services are provided. After users provide a retrieval keyword and the retrieval sub-surface information, the retrieval service interface returns the MOOC courses information lists and the courses sub-face aggregation results to the users.

Description

technical field [0001] The invention relates to a method for retrieving MOOC courses, in particular to a method for faceted retrieving MOOC courses based on ElasticSearch. Background technique [0002] As a crucial educational cooperation platform, MOOC China will lead China's distance education to the international stage. The combination of MOOC China and Silk Road College will become a brand-new model of Internet + education. With brand-new technology, resources, business and service concepts and means, it will realize the transformation and upgrading of online education and realize China's online education going to the world. [0003] ElasticSearch is a Lucene-based search server. It provides a distributed multi-user capable full-text search engine based on a RESTful web interface. ElasticSearch is developed in Java and designed for cloud computing. It can achieve real-time search, is stable, reliable, fast, easy to install and use, and is released as open source under ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06Q50/20
CPCG06F16/2228G06F16/244G06F16/2455G06F16/24556G06F16/24578G06Q50/2053
Inventor 刘均石磊魏笔凡王萌姚思雨曾宏伟郭朝彤王瑞杰
Owner XI AN JIAOTONG UNIV
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