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An Improved Collaborative Filtering Method Based on Mining Reviews and Correcting User Scores

A collaborative filtering and user commenting technology, applied in the information field, can solve the problems of ignoring the internal relationship between user comments and ratings, difficult to improve the accuracy of recommendation results, and not making full use of the interpretation function, achieving high practical value, improving credibility, The effect of improving quality

Active Publication Date: 2021-08-03
WUHAN UNIV OF TECH
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Problems solved by technology

Due to the limitation of the scoring rules (the rating is an integer of 1-5), and the overall quality of the product is good, the user's ratings are very concentrated, almost all of which are 5 points, and the degree of differentiation is very unclear
[0004] 2) The credibility of user ratings is not high, making it difficult to improve the accuracy of recommendation results
[0007] 3) The current collaborative filtering recommendation algorithm that considers user reviews and ratings ignores the inherent correlation between user reviews and ratings, and simply weights the two
Current recommendation algorithms that consider user reviews and ratings do not take full advantage of this explanatory power

Method used

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  • An Improved Collaborative Filtering Method Based on Mining Reviews and Correcting User Scores
  • An Improved Collaborative Filtering Method Based on Mining Reviews and Correcting User Scores
  • An Improved Collaborative Filtering Method Based on Mining Reviews and Correcting User Scores

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[0034] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0035] please see figure 1 , a kind of improved collaborative filtering method based on excavating comments and correcting user rating provided by the present invention, comprises the following steps:

[0036] 1) The characteristics and preferences that users pay attention to a certain type of product are stable for a period of time. In order to solve the "cold start" problem, all the user's comments on a certain type of product are obtained to form a comment set T u , scoring set V u ;

[0037] The ratings and comments in this embodiment are real user rat...

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Abstract

The invention discloses an improved collaborative filtering method based on excavating reviews and revising user ratings. First, word segmentation is performed on user review sets, and product feature words and corresponding emotional words in reviews are marked; for each review, the tagged in reviews are extracted Product feature words and corresponding emotional words, quantify the preference degree of the feature and the emotional strength of the emotional word, and establish the comment feature preference vector; calculate the emotional attitude of the comment according to the comment feature preference vector; correct the user rating according to the emotional attitude of the comment, and improve the rating. Discrimination and credibility; use the modified score to participate in collaborative filtering to generate recommendations. The invention can solve the problems of over-concentration and low reliability of current e-commerce website user ratings and improve the accuracy of collaborative filtering recommendation results.

Description

technical field [0001] The invention belongs to the field of information technology, and relates to an improved collaborative filtering method for correcting user ratings by mining user comment information, in particular to an improved collaborative filtering method for correcting user ratings by mining user comment information in e-commerce websites. Background technique [0002] Collaborative filtering algorithm is the most widely used recommendation algorithm in the field of recommendation system. Its characteristics are: by analyzing the user's historical data, constructing personal interest preferences, using other users with similar interests to recommend information that may be of interest to the target user. Collaborative filtering algorithms are divided into user-based collaborative filtering algorithms and content-based collaborative filtering algorithms. User-based collaborative filtering algorithms mainly use user ratings as the basis for constructing user inter...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q30/06G06Q30/00G06F40/30
CPCG06Q30/016G06Q30/0631G06F40/30
Inventor 王红霞陈健李玉强
Owner WUHAN UNIV OF TECH
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