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Commodity recommending method and commodity recommending system

A product recommendation and product technology, applied in the field of product application, can solve problems such as poor real-time performance, low product recommendation quality, and single recommendation service object, and achieve the effect of ensuring recommendation quality, real-time high-speed recommendation service, and strong scalability.

Inactive Publication Date: 2012-07-18
卓望数码技术(深圳)有限公司
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is to provide a product recommendation method and a product recommendation system for the defects of the prior art that the product recommendation quality is not high, the real-time performance is poor, and the object of the recommendation service is single

Method used

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  • Commodity recommending method and commodity recommending system
  • Commodity recommending method and commodity recommending system
  • Commodity recommending method and commodity recommending system

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Embodiment Construction

[0041] The present invention uses data mining technology for off-line modeling of users in WWW portals, WAP portals, and mobile terminal portals with login and subscription (browsing), without login and browsing, and with login without browsing and without ordering, combined with online recommendation calculations, using Memcached caching technology caches the recommendation results, provides different interfaces for different portals and different scenarios in the same recommendation distribution system, and provides recommended product data back to the major portals for display; introduces modern data mining technology data analysis mechanisms such as association and clustering, no need User preferences can be understood through user input; according to business scenarios and business support needs, other data mining technologies and statistical methods can also be used to arrange new communication interfaces for major online portals or offline systems.

[0042] figure 1 It ...

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Abstract

The invention relates to a commodity recommending method and commodity recommending system. The method comprises obtaining sample training data based on browsing history of users and / or user attributes, and establishing an associated analysis model for the sample training data; generating associated data based on the associated analysis model; accepting commodity recommending requests, and obtaining user information based on the commodity recommending requests, recommending commodities associated with the user information to relevant portals based on the user information and the associated data, so that relevant portals can show commodities to users. The commodity recommending system comprises a modeling unit and a commodity recommending server. The technical scheme not only guarantees recommending qualities, but also provides high-speed real-time recommending service, and has the advantages of being high in expandability, and suitable for different application contexts.

Description

technical field [0001] The present invention relates to the field of commodity application, and more specifically, to a commodity recommendation method and a commodity recommendation system. Background technique [0002] The product recommendation distribution system can recommend the right product to the user in the right scene. A common example is an e-commerce recommendation system, which recommends various products to users on the Internet, such as recommending new products on the shelves, discounted products, and hot-selling products. At present, the e-commerce recommendation system on the Internet generally recommends products based on product sales rankings and user evaluation scores for products. Due to the lack of intelligent analysis factors required for user personalized recommendations, in many cases the recommendation to users The product is not what the user likes. The current e-commerce recommendation system mainly has the following defects: [0003] 1) The...

Claims

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Application Information

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IPC IPC(8): G06Q30/00G06F17/30
Inventor 潘柱新吴亚雪龚剑辉曾华维
Owner 卓望数码技术(深圳)有限公司
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