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Dynamic recommendation method capable of adapting to user interest changes based on time information

A technology of user interest and time information, applied in the field of personalized recommendation, it can solve the problems of inaccurate recommendation and inability to recommend the latest items of users in time, and achieve the effect of alleviating the sparsity problem and achieving good benefits.

Active Publication Date: 2015-01-14
天津艺点意创科技有限公司
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Problems solved by technology

[0003] The traditional collaborative filtering recommendation algorithm analyzes the user's interest through the rating data generated by the user, and regards the user's rating at different times as the same weight. However, in the actual purchase behavior data, the user's interest is constantly changing, which causes Recommendations are inaccurate, and the latest items cannot be recommended to users in a timely manner

Method used

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  • Dynamic recommendation method capable of adapting to user interest changes based on time information
  • Dynamic recommendation method capable of adapting to user interest changes based on time information
  • Dynamic recommendation method capable of adapting to user interest changes based on time information

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Embodiment Construction

[0023] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0024] Such as figure 1 As shown, this method includes the following steps:

[0025] S10, define user set U={u 1 , u 2 ,...,u m}, m represents the total number of users, item set P={p 1 ,p 2 ,...,p n}, n represents the total number of items, and X represents the scoring item x i，j The m*n explicit scoring matrix, x i，j Indicates user i’s explicit rating on item j, where, 1≤i≤m, 1≤j≤n, x i，j The value range of is {1, 2, 3, 4, 5}. If a user i has not rated item j too much, then the corresponding matrix item x i，j Is empty. Therefore, the user-item explicit rating matrix X constructed b...

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Abstract

The invention relates to a dynamic recommendation method capable of adapting to user interest changes based on time information. The method comprises the steps that a user-object explicit rating matrix is built; a user-object implicit rating matrix is built; a user-object comprehensive rating matrix is built; similarity between two users is calculated; K users close to the target user similarity are obtained as the neighbour set of target users; a monotone decreasing exponential time function is selected as a rating weighting function, and the weighting factor of each user in the rating weighting function is calculated according to different interest change trends embodied by the scores of the users; a TOP-N recommendation method is adopted, and N objects with very top predication scores are recommended to the users. According to the method, the changes of the user interest along with time are considered, and the more precise personalized object recommendation service is provided for the users.

Description

technical field [0001] The invention relates to the technical field of personalized recommendation methods, in particular to a dynamic recommendation method based on time information that adapts to changes in user interests. Background technique [0002] With the vigorous development of information technology, a large amount of information is displayed in people's daily life. Traditional network services, such as catalogs and search engines, can no longer meet people's needs for information. Alleviating the problem of network information overload has become one of the main challenges at present. The recommendation system came into being under this background and is currently promoting the development of e-commerce. one of the effective ways. Its main task is to analyze the user's purchase behavior, clarify the user's purchase needs, and recommend to the user the products they are interested in but have not purchased. [0003] The traditional collaborative filtering recomme...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/00
Inventor 马廷淮郭莉敏唐美丽曹杰钟水明薛羽
Owner 天津艺点意创科技有限公司
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