Item recommendation method and system based on collaborative filtering algorithm

A project recommendation and project technology, applied in the project recommendation method and system field based on collaborative filtering algorithm, can solve problems such as heavy workload, long time consumption, and affecting the speed of recommendation generation, so as to reduce workload, solve speed bottlenecks, and ensure The effect of recommendation generation speed

Inactive Publication Date: 2016-08-03
SHANGHAI TRUELAND INFORMATION & TECH CO LTD
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Problems solved by technology

[0004] The existing above-mentioned entire recommendation process is completed online. However, with the expansion of the scale of the e-commerce system, the amount of data used to generate recommended it...

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  • Item recommendation method and system based on collaborative filtering algorithm
  • Item recommendation method and system based on collaborative filtering algorithm

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Embodiment Construction

[0040] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0041] The core of the present invention is to provide an item recommendation method and system based on a collaborative filtering algorithm, so as to reduce the workload of online recommendation and ensure the speed of recommendation generation.

[0042] In order to enable those skilled in the art to better understand the solution of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawin...

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Abstract

The invention relates to the technical field of automatic recommendation, and in particular relates to an item recommendation method and system based on a collaborative filtering algorithm. The method comprises the following steps: performing an cluster analysis on item scoring behaviors of m basic users offline to obtain k user clusters; determining a cluster center matrix Ckxn and a class subordination degree matrix Vmxk offline; carrying out an item recommendation on a target user by utilizing the cluster center matrix Ckxn and the class subordination degree matrix Vmxk online. By obtaining the k user clusters offline in advance, the cluster center matrix Ckxn and the class subordination degree matrix Vmxk are further obtained, and the working amount of online recommendation is reduced, so that the aim of guaranteeing a recommendation generation speed is realized, and a speed bottleneck problem caused by a traditional collaborative filtering algorithm in a recommendation generation speed is solved.

Description

technical field [0001] The invention relates to the technical field of automatic recommendation, in particular to an item recommendation method and system based on a collaborative filtering algorithm. Background technique [0002] Today, with the development of the Internet and e-commerce, the recommendation system has gradually become an important research content of e-commerce, and has attracted more and more researchers' attention. At present, almost all large-scale e-commerce systems, such as Amazon, CDNOW, eBay, etc., use various forms of automatic recommendation systems to varying degrees. [0003] In the existing item recommendation process based on collaborative filtering algorithm, firstly, the rating behavior of basic users is clustered through the ratings of basic users on items (such as commodities in e-commerce, movies, music, web pages and documents, etc.) Analysis, the basic users are divided into several categories, combined with the collaborative filtering ...

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/285G06F16/9535
Inventor 袁文涛董启文
Owner SHANGHAI TRUELAND INFORMATION & TECH CO LTD
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