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Method for recommending commodities to customers

A product and customer technology, applied in the field of recommending products to customers, can solve the problem of not considering the impact of the accuracy of the recommendation system

Inactive Publication Date: 2012-07-11
尚明生
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

[0011] However, in the prior art, this general method of sorting recommended products according to the predicted score value only considers the individual needs of a single customer this time, and does not consider the impact of recommended products on the accuracy of the entire recommendation system.

Method used

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  • Method for recommending commodities to customers
  • Method for recommending commodities to customers
  • Method for recommending commodities to customers

Examples

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example

[0080] A practical example is used below to illustrate the implementation process of the present invention.

[0081] To simplify the description, in this example, there are 4 customers and 5 movies in the recommendation system of the e-commerce website, and the movies are commodities purchased by the customers. As shown in Table 1, the middle row in Table 1 represents the customer, and the column represents the movie. The value in the corresponding cell is the customer’s rating of the movie. If the cell is empty (-), it means that the customer has not watched the movie, so Constitute the customer movie rating matrix R in Table 1.

[0082]

[0083] Table 1

[0084] Suppose customer u 5 is the target customer, as can be seen from Table 1, the target customer u 5 The list of watched, i.e. purchased items, i.e. movies is {o 1 , o 2}. The present invention provides the target customer u with two steps 5 Recommend movies: first calculate the target customer u 5 The list o...

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Abstract

The invention discloses a method for recommending commodities to customers. The method comprises the following steps of: calculating predicted scoring values of target customers on all un-scored commodities according to a set of commodities purchased by the target customers and a corresponding scoring value set, and selecting K commodities with maximum scores as a candidate recommended commodity set by a candidate commodity calculating module; and adding the predicted scoring value of each candidate commodity of the target customers as an actual score of the target customers into a system, calculating the predicted values of the purchased commodities, calculating the evaluation indexes of corresponding prediction accuracy, sequencing the candidate commodity set according to the advantages and the disadvantages of the acquired evaluation indexes, and thus acquiring a final recommending list by a candidate commodity sequencing module. By the method, the candidate commodities with best system evaluation indexes are sequenced in the front of the list, so that the individual requirements of the customers are met, and the recommending accuracy of the whole system is improved.

Description

technical field [0001] The invention belongs to the technical field of information and e-commerce, and more specifically relates to a method for recommending commodities to customers in an e-commerce website recommendation system. Background technique [0002] With the rapid development of WEB technology, the information on the Internet is becoming more and more abundant. However, these kinds of information, while making it convenient for people to obtain information, have also brought about a serious problem of information overload. The so-called information overload refers to the fact that there are too many available information, even exceeding the individual's thinking and processing ability, so that although people are faced with a lot of information, it is often difficult to determine which information is really needed. [0003] In order to help users find useful information from massive network data (information), two schemes have been widely adopted. [0004] One i...

Claims

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Application Information

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IPC IPC(8): G06Q30/02
Inventor 王庆先尚明生
Owner 尚明生
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