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Shopping search recommendation and warning method and system

A search recommendation and recommendation degree technology, applied in the Internet field, can solve problems such as difficulty in meeting user needs, inability to quickly select and purchase suitable products, poor user purchase and search experience, etc.

Active Publication Date: 2017-08-25
上海同刚网络科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In this way, the current shopping search engine only stays at the stage of simple related inquiries such as price comparison, reputation comparison, and sales volume. Users must judge the quality of a product and service quality by themselves, requiring a lot of browsing products and reading reviews. Therefore, it is impossible to quickly select and purchase. suitable product
With the improvement of users' requirements for shopping experience and product quality, based on the existing search methods, the user's purchase and search experience is poor, and it is difficult to meet user needs

Method used

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  • Shopping search recommendation and warning method and system
  • Shopping search recommendation and warning method and system
  • Shopping search recommendation and warning method and system

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[0053] The term "recommendation degree P3" refers to the degree of recommending users to buy, divided into 6 levels, corresponding to 0, 0.2, 0.4, 0.6, 0.8, 1 (the larger the value, the more worth buying), and it is displayed in the form of a picture, where "0" Replace with a sheet of 5 hollow icons, "0.2" is replaced with a sheet of 1 solid and 4 hollow icons, and so on, "1" is replaced with a sheet of 5 solid icons; the term "cheating rate P1" is the alarm level, Divided into 6 levels, corresponding to 0, 0.2, 0.4, 0.6, 0.8, 1 (the greater the value, the higher the shopping risk), and displayed in the form of a picture, in which "0" is replaced by a piece of 5 hollow icons, "0.2 "Replace with 1 solid and 4 hollow icons, and so on, "1" is replaced with 5 solid icons, where the expressions of "recommendation P3" and "cheating rate P1" are not limited to icons or numbers. It is only one of the division forms and representation methods for the convenience of users to understand,...

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PUM

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Abstract

The invention relates to a shopping search recommending and alarming method and system and relates to the technical field of Internet. The method comprises the following steps: in a background pre-treatment stage, S101, capturing raw information from shopping websites by virtue of a crawler system; S102, directly storing the raw information so as to update a database center; S103, obtaining the sum X of negative comments according to a predefined semantic analysis model; S104, calculating the cheating rate P1; S105, calculating to obtain the sum Z of positive comments according to the predefined semantic analysis model; S106 calculating to obtain a recommendation level P3; storing the cheating rate P1 and the recommendation level P3 in the data center so as to update the data center; S109, providing information to the client by virtue of the search websites after the data center is updated in real time; S110, providing browsing for users by the client according to the cheating rate P1 and the recommendation level P3 provided. The interactive shopping search recommending system comprises a crawler system, a pre-treatment center, a data center and search and result display websites; the risk that the user is cheated in shopping is reduced.

Description

technical field [0001] The invention relates to the technical field of the Internet, in particular to an interactive shopping search recommendation and warning method and system. Background technique [0002] With the rapid development of Internet shopping and the continuous increase of stores and platforms, users' requirements for product search are also constantly increasing, and they also pay more attention to product quality and service requirements. [0003] Existing shopping search engines use crawler systems to capture product information and attributes such as product name, price, sales volume, reputation, etc. from various shopping websites, and hand them over to the processing center to calculate product categories and sorting weights (preprocessing), and then upload the original The product information and attributes obtained after preprocessing, as well as the product category and sorting weight information obtained after preprocessing, are all stored in the data...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30G06Q30/02G06Q30/06
CPCG06F16/9535G06Q30/0601
Inventor 肖俊
Owner 上海同刚网络科技有限公司
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