Intelligent semantic document recommendation method and device and computer readable storage medium

Abstract

The invention relates to the technical field of voice semantics, and discloses an intelligent semantic document recommendation method, which comprises the following steps of obtaining all document information in a document database as a training set; acquiring historical query information of a user and document information selected by the user in history, and performing preprocessing operation onthe historical query information and the document information selected by the user in history to obtain feature points serving as a tag set; using the training set and the label set to train the constructed intelligent semantic document recommendation model; and receiving query information input by the user, performing document retrieval from the document database by utilizing the intelligent semantic document recommendation model, sorting document retrieval results, and outputting the sorted document retrieval results to the user. The invention further provides an intelligent semantic document recommendation device and a computer readable storage medium.

Description

technical field [0001] The present invention relates to the technical field of speech semantics, in particular to an intelligent semantic document recommendation method, device and computer-readable storage medium based on knowledge content and user behavior collaboration. Background technique [0002] Speech skills show the way people think about problems and speak. Some people speak in a straight line, and the listener can clearly understand and understand what the speaker wants to express, and give correct feedback, while some people speak as if Nowhere near the itch, it is necessary to have a deeper understanding of what the speaker wants to express in order to give correct feedback. [0003] When a user needs to consult a certain aspect of information, in view of the user's usual way of thinking and speaking, according to the document information entered by the user in the search box, traditional document search methods such as cosine similarity, Jaccard Distance, VSM,...

AI Technical Summary

Problems solved by technology

[0003] When a user needs to consult a certain aspect of information, in view of the user's usual way of thinking and speaking, according to the document information entered by the user in the search box, traditional document search methods such as cosine similarity, Jaccard Distance, VSM, etc., the information searched and recommended to the user may not match the information the user really needs, thus wasting the user's energy and time, and bringing a bad user experience to the user

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