Score prediction method, apparatus, computer equipment and storage medium

A score prediction and mechanism technology, applied in the computer field, can solve problems such as poor score prediction ability and low accuracy rate, and achieve the effect of improving score accuracy
CN110866637BActive Publication Date: 2022-07-05HUNAN UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
HUNAN UNIV
Publication Date
2022-07-05

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Abstract

The present application relates to a scoring prediction method, device, computer equipment and storage medium. By receiving a user ID and an item ID, user preference features and item preference features, as well as user-corresponding review information and item-corresponding review information are obtained; based on the text feature matrix; obtain the usefulness of review information according to the text feature matrix, user preference features and item preference features; obtain the swarm wisdom feature according to the review information usefulness and text feature matrix; map the user preference feature and item preference feature to the swarm wisdom feature The feature space is obtained to obtain user hidden features and item latent features; and then obtain the user's predicted score for the item. The present application obtains the group wisdom feature through the comment information of the user and the item, and then extracts the latent feature of the item through the group wisdom feature to obtain the matching score between the user and the item, which can effectively improve the scoring accuracy of the recommendation system.
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Description

technical field

[0001] The present application relates to the field of computer technology, and in particular, to a score prediction method, apparatus, computer equipment and storage medium. Background technique

[0002] With the rapid development of information technology and the Internet, online shopping has also become the main way for people to shop. After the user purchases the product, they will rate the product and write a review to express their opinion. Among them, the score describes the degree that the user likes the product, and the comment information describes the specific reason why the user likes the product or dislikes the product. When shopping online, user comments on products on e-commerce websites or APPs can help other potential consumers understand the whole picture of the product and help potential consumers make purchasing decisions.

[0003] However, the existing rating prediction methods are mainly based on topic models to model text reviews, and...

Claims

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