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Characteristic-based collaborative filtering recommendation method

A collaborative filtering recommendation and variance technology, applied in the field of e-commerce-based recommendation applications, can solve problems such as difficult to determine and difficult to describe and represent products

Inactive Publication Date: 2014-02-05
FOCUS TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Collaborative filtering algorithm makes up for the shortcomings of content-based algorithms: some products are difficult to describe and express
However, this threshold is difficult to determine

Method used

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Embodiment Construction

[0113] The present invention will be further elaborated below in conjunction with the accompanying drawings and specific embodiments.

[0114] English proper words and abbreviations correspond to Chinese meanings

[0115] Recommendation system (RS) Recommended system Recommendation algorithm (RA) recommendation algorithm Collaborative filtering (CF) Collaborative filtering Feature-based Collaborative Filtering (FCF) Feature-Based Collaborative Filtering E-commerce (EC) e-commerce User user Item product Features Attributes User based filtering user-based filtering Item base filtering Product Based Filtering Mean absolute error (MAE) mean absolute error

[0116] 1. Design of feature-based collaborative filtering method

[0117] In the content-based recommendation method, the features of the items are extracted, and the items similar to the purchased items are recommended to the user by calculat...

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Abstract

The invention pertains to the recommendation system field in the information technology, and is particularly suitable for the recommendation application based on an e-commerce platform in an Internet environment. For shortages with existing collaborative filtering methods, a new characteristic-based collaborative filtering method is provided. According to the new method, the likes and dislikes of article characteristics of users in the goods purchasing process are fully taken into consideration, so a recommendation result which is a more accurate than a conventional collaborative filtering method in the condition that less neighbours of users / products are used, so that the recommendation system is more close to potential demands of website users. Overall, the new method is a collaborative filtering recommendation method having advantages of high efficiency and wide application range.

Description

technical field [0001] The invention belongs to the technical field of recommendation systems in information technology, and is particularly suitable for recommendation applications based on e-commerce under the Internet environment. Background technique [0002] The emergence and rapid development of online shopping not only provide people with richer and more diverse product information, but also make it difficult for people to find the product they really want when faced with many choices. The most popular and effective solution to this information overload is recommender systems. The recommendation system can automatically push personalized products to customers to reduce customers' browsing time and improve shopping efficiency. The essence of the recommendation system is to predict a customer's evaluation of a product based on the customer's historical records, and recommend products that he may be interested in or highly rated according to the predicted results. A re...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02
Inventor 周水庚关佶红李丹青朱晓然周晔王海清
Owner FOCUS TECH
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