Official document recommendation method and device based on graph structure, computer equipment and medium

Abstract

The invention relates to the field of big data, and discloses an official document recommendation method and device based on a graph structure, computer equipment and a medium. The official document recommendation method comprises the steps: acquiring multiple official documents, screening feature words according to TF-IDF, and recording the feature words as keyword tags of the official documentscorresponding to the feature words; screening out text topics of which the selection probabilities are greater than or equal to a preset probability through the text topic-keyword distribution probability matrix of the official document, and recording the screened text topics as topic tags of the official document corresponding to the screened text topics; generating official document attributes according to the keyword tags and the topic tags; acquiring record data of the official document, and establishing an official document recommendation library based on a graph structure through a Neo4jframework according to the record data of the official document and official document attributes; and receiving retrieval content input by the user from the official document recommendation library,and outputting a target official document according to the similarity sequence calculated by the SimRank. According to the official document recommendation method and device, the target official document with the highest relevancy with the retrieval content input by the user can be recommended to the user.

Description

technical field [0001] The present invention relates to the field of data analysis in the field of big data, in particular to a method, device, computer equipment and medium for recommending official documents based on a graph structure. Background technique [0002] At present, most of the common document recommendation methods are based on traditional search engines. When traditional search engines recommend official documents, they usually recommend based on the similarity of official documents. In this way, official documents with high relevance to users can be recommended. However, in the existing technology, The determination of the similarity of official documents is often based on a single standard manually set. In this way, due to the fact that the standard manually set may be inaccurate, it will lead to incomplete consideration when traditional search engines recommend official documents. This problem leads to the inability to recommend to the user the official doc...

AI Technical Summary

Problems solved by technology

[0002] At present, most of the common document recommendation methods are based on traditional search engines. When traditional search engines recommend official documents, they usually recommend based on the similarity of official documents. In this way, official documents with high relevance to users can be recommended. However, in the existing technology, The determination of the similarity of official documents is often based on a single standard manually set. In this way, due to the fact that the standard manually set may be inaccurate, it will lead to incomplete consideration when traditional search engines recommend official documents. problem, which leads to the inability to recommend to the user the official document with the highest degree of relevance to the content entered by the user, which affects the user experience effect

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