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A recommendation method and recommendation item technology, applied in the computer field, can solve the problem of low recommendation adoption rate
Active Publication Date: 2020-06-23
SHENZHEN UNIV
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[0004] The purpose of the present invention is to provide a recommendation method and device, which aims to solve the problem that it is difficult to make accurate, novel and comprehensive personalized recommendations in the prior art, resulting in a low adoption rate of recommendations
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Embodiment 1
[0026] figure 1 The implementation flow of the recommendation method provided by Embodiment 1 of the present invention is shown. For the convenience of description, only the parts related to the embodiment of the present invention are shown, and the details are as follows:
[0027] In step S101, historical recommendation preference data is received, and extreme points of recommendation targets are obtained according to the historical recommendation preference data, wherein the recommendation targets include accuracy, coverage and diversity.
[0028] In the embodiment of the present invention, the recommendation target refers to the requirements that need to be met when obtaining the products recommended to the user. These requirements include accuracy, coverage and diversity, that is, the products recommended to the user need to meet the accuracy, coverage and diversity. requirements. Pre-provide historical preference data of all users on items (for example, commodities), tha...
Embodiment 2
[0047] figure 2 The structure of the recommendation device provided by Embodiment 2 of the present invention is shown. For the convenience of description, only the parts related to the embodiment of the present invention are shown, including:
[0048] The extreme point acquisition unit 21 is configured to receive historical recommendation preference data, and acquire extreme points of recommendation targets according to the historical recommendation preference data, wherein the recommendation targets include accuracy, coverage and diversity.
[0049] In the embodiment of the present invention, all users' historical preference data for items (for example, commodities) are provided in advance, that is, historical recommendation preference data. After receiving the historical recommendation preference data, the extreme point acquisition unit obtains the recommended target extremum point. Preferably, the degree of preference in the historical preference data of all users for com...
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Abstract
The invention is suitable for the technical field of computer, and provides a recommendation method and device. The method comprises the following steps of: receiving history recommendation preference data; obtaining an extreme point of a recommendation target; generating a corresponding current population; calculating a target function value of the current population; selecting a preset quantity of individuals from the current population according to the target function value to group a parent population; carrying out an evolution operation on the parent population; generating a child population; when the current evolution algebra does not exceed a preset evolution algebra threshold value, combining the parent population and the child population to generate a next generation of evolution population; setting the next generation of evolution population as the current population; adding 1 to the current evolution algebra; calculating the target function value of the current population again; repeating the steps until the current evolution algebra achieves an evolution algebra threshold value; and setting the parent population as a recommendation result so as to realize correct, novel and comprehensive personalized recommendation and then improve the recommendation adoption rate.
Description
technical field [0001] The invention belongs to the technical field of computers, and in particular relates to a recommendation method and device. Background technique [0002] In the era of information overload, it is difficult for users to select the content they are interested in from the massive amount of information, which prompts many scholars to invest in the research of recommendation technology. Recommendation technology is a technology based on statistics and knowledge discovery to recommend content of interest to users. It aims to help users find the information they are interested in and reduce the time it takes for users to locate and search for information. For example, e-commerce sites recommend products to users based on their purchase records, social networking sites analyze our newsletter directories to help us meet new friends, and e-educational institutions help learners choose courses, topics, or learning materials they are interested in. [0003] At pr...
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