Collaborative filtering recommendation method based on item energy diffusion and user preference

A collaborative filtering recommendation and energy diffusion technology, applied in the recommendation field, can solve the problems of not considering the differences of users and items, poor diversity, etc., and achieve the effect of improving high precision and high diversity

Inactive Publication Date: 2019-02-05
LIAONING NORMAL UNIVERSITY
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AI Technical Summary

Problems solved by technology

However, in the energy diffusion process of this method, whether it is an item to a user or a user to an item, the average diffusion is performed, and the difference between the user and the item is not considered, and the different energy of the item initialization will produce different recommendation results. Therefore, the items recommended by this method are often popular items, and the diversity of recommendations is poor.

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  • Collaborative filtering recommendation method based on item energy diffusion and user preference
  • Collaborative filtering recommendation method based on item energy diffusion and user preference
  • Collaborative filtering recommendation method based on item energy diffusion and user preference

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Embodiment Construction

[0042] A collaborative filtering recommendation method based on item energy diffusion and user preference in the present invention is as follows: figure 1 As shown, follow the steps below:

[0043] make U={U 1 ,U 2 ,…,U m } represents a collection of users, where m represents the total number of users, U u Indicates the first u users, 1≤u ≤m ; U tu represents the target user, 1≤tu≤m ;make I={I 1 ,I 2 ,…I n } represents a collection of items, where n Indicates the total number of items, I i Indicates the first i items, 1≤i≤n ;make R∪{*} Indicates the user's rating set for the item, where * indicates that the user has not rated the item; let the user U u ∈U to items I i ∈I rated by r u,i ∈R∪{*} ;make k ( I tu ) = { I i ∈I | r tu,i = *} indicates the target user U tu The collection of unrated items for , where I ti ∈k ( I tu ) is the target user U tu The unrated item set of ti items;

[0044] Step 1. Count the rating in...

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Abstract

The invention discloses a collaborative filtering recommendation method based on article energy diffusion and user preference, which can simultaneously provide high-precision and high-diversity recommendation. A bipartite diagram of an article; Initializing the energy of the article, and diffusing the initial energy of each article to the article through the user according to the energy diffusionprinciple and the user preference; According to the specific gravity of energy diffusion between articles, the similarity between articles is calculated, and the adjacent articles are selected. For the unscoring items of the target user, the prediction scoring is performed according to the scoring of the neighboring items of the target user. The N items with the highest prediction score were selected and recommended to the target users.

Description

technical field [0001] The invention relates to the technical field of recommendation, in particular to a collaborative filtering recommendation method based on item energy diffusion and user preference that can simultaneously provide high-precision and high-diversity recommendations. Background technique [0002] With the development of mobile smart devices, data is growing at an explosive rate, and people cannot quickly and accurately find the information they need from the massive amount of information, resulting in the phenomenon of "information overload". The recommendation system can perceive the user's needs according to the user's personal information, intelligently and quickly recommend valuable information to the user, and solve the "information overload" problem. [0003] Item-based collaborative filtering is one of the most widely used recommendation techniques in recommendation systems. This method assumes that if an item is similar to an item that the user lik...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/06
CPCG06Q30/0631
Inventor 张志鹏任永功邹丽张大为
Owner LIAONING NORMAL UNIVERSITY
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