Personalized recommendation method based on commodity property entropy

A product attribute and recommendation method technology, applied in marketing and other directions, can solve problems such as low efficiency of content recommendation, achieve the effect of maintaining the recommendation hit rate, effective recommendation, and improving diversity

Inactive Publication Date: 2012-04-11
NANJING UNIV
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Problems solved by technology

However, due to the increasing number of product attributes, the user profile based on product attributes has become increasingly larg

Method used

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  • Personalized recommendation method based on commodity property entropy
  • Personalized recommendation method based on commodity property entropy
  • Personalized recommendation method based on commodity property entropy

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[0034] The present invention proposes a new way of analyzing user profile, figure 2 This is an example of the user profile of the present invention. The figure shows a user profile with five attribute classifications and the statistics of brand attribute labels. The statistics of each attribute classification will finally be transformed into the entropy value of the corresponding classification. It is a user in a broad sense, so the global entropy value can also be obtained using this method. According to the user's entropy value in different classifications, combined with the entropy value of the overall classification, the user classification entropy value is converted into weight. Use weights to calculate the similarity between the products in the recommended candidate set and the products seen by the current user to complete the rearrangement of the original recommendation sequence. This method tends to recommend relatively unpopular products to users, thereby providing use...

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Abstract

The invention relates to a personalized recommendation method based on commodity property entropy. The method comprises the following steps of: achieving the browsing history of electronic commerce website users through a script; analyzing the browsing history; and generating a recommendation result and performing personalized recommendation. In the method, the user profile based on the commodity property entropy can help the recommendation calculation method to find the preference of the users in different property classification, and different recommendation is generated by utilizing the information of the users in the browsing process and according to the actual selection of the users, so that diversity of the commodity page recommendation is improved. Based on a recommendation system requiring personalized recommendation, the hit rate of recommendation is maintained and recommendation diversity is improved. By the method, on the premise of not changing greatly, the results generated by other recommendation calculation methods are sequenced again, so that the effect of the original recommendation calculation method is not influenced, diversity of the commodity page personalized recommendation is improved, and recommendation on the commodity pages is more effective.

Description

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Claims

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Application Information

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Owner NANJING UNIV
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