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A Product Attribute Clustering Method Based on User Comments

A technology of product attributes and user reviews, applied in text database clustering/classification, business, data processing applications, etc., can solve the problem that products cannot truly reflect user reviews, and achieve the effect of improving shopping experience and saving time.

Inactive Publication Date: 2017-08-01
BEIJING INSTITUTE OF TECHNOLOGYGY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention provides a product attribute clustering method based on user comments to solve the problem that the recommended products cannot truly reflect user evaluations for users with clear purchase goals in the existing recommendation system, and to help users quickly select products

Method used

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  • A Product Attribute Clustering Method Based on User Comments
  • A Product Attribute Clustering Method Based on User Comments
  • A Product Attribute Clustering Method Based on User Comments

Examples

Experimental program
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Embodiment Construction

[0035] Such as figure 1 As shown, it is a flow of a clustering method based on user comments and commodity attributes described in the embodiment of the present invention. In combination with examples, the present invention is described in detail:

[0036] According to step 1, Amazon collects product attribute information and review information for computer products in the field of electronic products, and the attribute information includes CPU, screen, memory, graphics card, etc. Commodity attribute tree such as figure 2 shown.

[0037] According to the second step, the comment information and rating information of the product are preprocessed to extract the key features of the user comments. in:

[0038] 1. Remove spam comments from product comment information first. Use the keyword filtering technology to delete the sentences including S={advertisement, contact address, consultation phone number, no advantages and disadvantages found for the time being...} in the evalu...

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Abstract

The invention relates to a commodity property clustering method based on user comments, and belongs to the field of data mining. The method comprises the following steps: combining user comments information and commodity property information; calculating the feedback rates of the properties of commodities with similar characteristics according to the user comments; calculating the similarity of the commodities by taking the feedback rate as a weight; re-sequencing the commodities; returning needed commodities comprising real information to a user. By adopting the commodity property clustering method, commodities with most real good comments can be directly screened in concerned commodity properties of the user, so that the commodity selecting and purchasing time is saved, and the shopping experience of the user is improved.

Description

technical field [0001] The invention relates to a commodity attribute clustering method based on user comments, which belongs to the field of data mining. Background technique [0002] Since the 1990s, with breakthroughs in network, communication and information technology, the Internet has grown explosively and spread rapidly around the world. Under this premise, e-commerce came into being. E-commerce activities are a modern way of conducting business activities through public computer communication networks. This way breaks through the time and geographical limitations of traditional commerce and becomes a convenient, fast, safe and reliable emerging electronic business activity mode. Buyers and sellers can conduct business activities such as online shopping and electronic payment without leaving home in an open network environment. [0003] With the continuous development of e-commerce and the continuous expansion of the scale, the number and types of goods are also inc...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30G06Q30/02
CPCG06F16/35G06Q30/0255
Inventor 闫波张也宿红毅郑宏
Owner BEIJING INSTITUTE OF TECHNOLOGYGY