Information recommendation system and information recommendation method

Abstract

The invention relates to the technical field of the internet, in particular to a recommendation system and a recommendation method for a website provision object. An information recommendation system comprises a data module used for collecting and storing attribute data of users and extracting and analyzing keywords of orders, a triggering module used for generating recommended candidate sets by utilizing a triggering policy, a screening module used for fusing the recommended candidate sets and filtering commodities which do not meet recommendation conditions, a sorting module used for performing priority re-sorting on commodities to be recommended to the users, and a recommendation module used for recommending the sorted commodities to the users. According to the system and the method, commodities related to commodities browsed or purchased by the users can be recommended to the users, so that the diversity of recommendation is greatly enhanced, the commodities purchased by the users are not repeatedly recommended, a recommendation function is optimized, the conversion from recommendation to sale is promoted, and the conversion rate of sale and the usage rate of the users are increased.

Description

[0001] 【Technical field】 [0002] The invention relates to the technical field of the Internet, in particular to a recommending system and a recommending method for objects provided by a website. [0003] 【Background technique】 [0004] In the Internet era of excess information, the importance of information recommendation technology to the operation of Internet companies is self-evident. At present, various websites use recommendation systems in the background, and "Today's Recommendation" and "Guess You Like" are launched. Two functions, such as various shopping websites, paid download music websites, video websites and various service websites, etc., they calculate the most suitable candidate products recommended to the user according to the user's access characteristics, and then list these products displayed to the user for selection. Due to the huge number of products and users, the recommendation system extensively uses data mining based on cloud computing. By mining us...

AI Technical Summary

Problems solved by technology

This kind of recommendation is not personalized enough, the diversity of recommended products is not enough, and the potential needs of users for other products cannot be discovered, because users tend to be less interested in products they have already purchased.

In addition, the recommendation system of most websites on the Internet is mainly based on Baidu plug-ins, which cannot really achieve the purpose of turning recommendation into operation

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