Recommendation algorithm based on multi-index grading

A multi-indicator scoring and recommendation algorithm technology, applied in computing, special data processing applications, instruments, etc.

Inactive Publication Date: 2015-11-25
SOUTH CHINA UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a recommendation algorithm based on multi-index scoring to solve the problem of personalized recommendation that users may have different index preferences for different commodities

Method used

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  • Recommendation algorithm based on multi-index grading
  • Recommendation algorithm based on multi-index grading
  • Recommendation algorithm based on multi-index grading

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Embodiment Construction

[0077] The present invention will be further described below in conjunction with specific examples.

[0078] Such as figure 1 As shown, the recommendation algorithm based on multi-index scoring described in this embodiment includes the following steps:

[0079] 1) Identification of index keywords

[0080] When a user writes a product review, in addition to directly commenting on the index of the product, he will also comment on the relevant features under the index. For example, when a hotel user comments on the service indicator, the user may also mention other service-related features, such as "allthestaffwerebrilliant", where "staff" is the feature keyword related to the service indicator. Obviously, whether it is the indicator itself or the characteristic keywords related to the indicator, the user's opinion on them should be used to calculate the opinion score of the indicator. Therefore, we use an algorithm based on the self-increasing model to evaluate the key of the ...

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Abstract

The invention discloses a recommendation algorithm based on multi-index grading. The recommendation algorithm comprises the following steps of firstly, recognizing index keywords, secondly, extracting suggestion grading, thirdly, constructing a user and commodity similarity matrix, fourthly, using a two-way clustering algorithm for obtaining a clustering matrix, fifthly, conducting single in-cluster recommendation and sixthly using a comprehensive function algorithm for obtaining a final recommendation result. According to the recommendation algorithm, the problem that a user may need individual recommendations for different index preferences for different commodities can be solved, the high accuracy is achieved, and the recommendation result with the higher quality can be obtained.

Description

technical field [0001] The invention relates to the technical field of e-commerce recommendation systems, in particular to a recommendation algorithm based on multi-index scoring. Background technique [0002] By actively pushing information or services that users may be interested in, the recommendation system helps users obtain more useful information and saves retrieval time. The realization of traditional recommendation systems mainly relies on collaborative filtering technology. Although it has achieved success within a certain range, collaborative filtering technology often only uses a single comprehensive score to describe the user's preferences, and the comprehensive score can only describe the degree to which the user likes a product. , but doesn't know anything about why the user liked the item. In order to describe the user's preference information in more detail and improve the accuracy of the recommendation results, the emerging recommendation system should foc...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 陈健林世杭
Owner SOUTH CHINA UNIV OF TECH
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