A content-based novel recommendation method

A recommendation method and novel technology, applied in the fields of instrumentation, calculation, electrical digital data processing, etc., to solve the problem of low recommendation accuracy and increase accuracy and flexibility

Active Publication Date: 2021-10-22
KUNMING UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a content-based novel recommendation method in view of the limitations and deficiencies of the prior art, so as to solve the problems of low recommendation accuracy, weak classification ability, and low efficiency when recommending novels in the prior art. Inferior phenomenon, working to increase the accuracy and flexibility of novel recommendations that currently rely on computers

Method used

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  • A content-based novel recommendation method
  • A content-based novel recommendation method
  • A content-based novel recommendation method

Examples

Experimental program
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Embodiment 1

[0033] Embodiment 1: as Figure 1-3 As shown, a novel recommendation method based on content first initializes the novel text and extracts the corresponding SinHash fingerprints to establish a dynamic novel database; then enters the reference novels, and passes the publication time of the novels and novel texts based on the SinHash fingerprint correlation degree to determine the novels to be recommended; finally, the novels to be recommended are sorted by relevance, and the recommended novels with certain items are output.

[0034] Specifically include the following steps:

[0035] Step0: Get the novel text collection {X 1 ,X 2 …X p}, for novel text X, X∈{X 1 ,X 2 …X p} Perform preprocessing and establish a dynamic novel database, as shown in Step0.1 to Step0.5;

[0036] Step0.1: Extract the novel name x and the publication time tx of the novel from the novel text X;

[0037] Step0.2: Perform word segmentation, stop word removal, and synonym replacement on the novel te...

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Abstract

The invention relates to a content-based novel recommendation method, belonging to the technical field of recommendation methods. First, initialize the novel text and extract the corresponding SinHash fingerprints to establish a dynamic novel database; then input the reference novels, and determine the novels to be recommended by the publication time of the novels and the correlation between the novel texts based on the SinHash fingerprints; finally, the recommended novels are correlated Sort by degree and output the recommended novels of a certain item. Compared with the prior art, the present invention mainly solves the problems of low recommendation accuracy, weak class discrimination ability, and poor efficiency in the prior art when recommending novels, and increases the accuracy and efficiency of recommending novels by relying on computers at present. flexibility.

Description

technical field [0001] The invention relates to a method for recommending novels based on content, and belongs to the technical field of recommendation methods. Background technique [0002] Recommendation algorithms are flooded in every corner of the Internet system, usually according to the needs of users, the system recommends relevant content for them. In text recommendation methods such as novels and books, a keyword recommendation algorithm is usually used, that is, to recommend other novels with the same keywords according to the keywords of the novel. [0003] However, the content recommended by the keyword-based recommendation algorithm sometimes does not meet people's needs, and people are more willing to find other novels with the same style and similar genre as the novels they have read. Contents of the invention [0004] The technical problem to be solved by the present invention is to provide a content-based novel recommendation method in view of the limitat...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/335G06F16/9535G06F16/9536
Inventor 吴晟韩林峄
Owner KUNMING UNIV OF SCI & TECH
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