Personalized Recommendation Method

A recommended method and user technology, applied in special data processing applications, instruments, electrical digital data processing, etc., to achieve the effect of improving effectiveness

Active Publication Date: 2018-05-15
TSINGHUA UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Therefore, the items a user has used will not equally reflect the user's preferences at a given moment

Method used

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Embodiment Construction

[0024] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0025] see figure 1 , a personalized recommendation method described in this program, specifically including:

[0026] Step S101, acquiring the user's use behavior data on the item;

[0027] Step S102, generating a user usage behavior sub-list according to the acquired usage behavior data;

[0028] Step S103, traversing the generated user behavior sub-list, estimating the one-step transition probability matrix of the item;

[0029] Step S104, establishing a personalized recommendation model based on the forgetting process of the user's interest in the item and the Markov model;

[0030] Step S105, using the gradient descent method to estimate the user's personalized parameters in the process of forgetting the interest, so as to...

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Abstract

The invention discloses an individual recommendation method, and relates to the technical field of computer data processing. The individual recommendation method includes the steps that usage behavior data of a user to goods are obtained; a sub list of the usage behavior data of the user is generated according to the obtained usage behavior data; the generated sub list of the usage behavior data of the user is traversed, a matrix of transition probability of the goods is estimated; an individual recommendation model is established based on the interest in the goods forgetting process of the user and the Malko model; by using a gradient-descent method, individual parameters of the user are estimated in the interest forgetting process, a recommendation to the users is carried out according to the usage of the behavior sub list of the user. The individual recommendation method can catch preferential dynamic changes of the user more accurately and even more seems to have practical value.

Description

technical field [0001] The invention relates to the technical field of computer data processing, in particular to a personalized recommendation method. Background technique [0002] With the rapid development of the Internet, people's daily life is more and more closely connected with the Internet, such as listening to music, watching movies, shopping, reading, chatting and so on. At the same time, massive amounts of user and item data are continuously generated on the Internet every day, which makes it difficult or even impossible for Internet users to quickly find the unknown information they need or are interested in. As a result, personalized recommendation technology came into being, and it continues to introduce new ones. Personalized recommendation technology aims to model the user's interest preferences according to the user's own characteristics, and then recommend items that meet the user's personalized preferences and have not yet been used. [0003] Collaborati...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30G06K9/62
Inventor 王朝坤陈俊王建民
Owner TSINGHUA UNIV
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