Tripartite graph news recommendation method based on time weighting
A time-weighted, recommendation method technology, applied in instruments, unstructured text data retrieval, calculation, etc., can solve the problems of affecting recommendation accuracy, not taking into account the rationality and accuracy of labels, and poor recommendation effect, and achieving high accuracy accurate effect
Active Publication Date: 2022-06-21
CHONGQING UNIV OF POSTS & TELECOMM
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[0004] However, in the recommendation process, this method does not consider the rationality and accuracy of the label itself; at the same time, the patent only considers the weight of the label, but does not determine the importance between users and news; all users and News is recommended with the same weight, which will affect the accuracy of the recommendation and lead to poor recommendation results
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[0050] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described examples are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.
[0051] The present invention is a three-part graph news recommendation method based on time weighting, such as figure 1shown, including:
[0052] Input the obtained news data browsed by the user, calculate the optimized news resource value according to the obtained news data browsed by the user; perform news recommendation according to the optimized news resource value;
[0053] The news data browsed by the user includes browsing time, news title and news text;
[0054] The proc...
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The present invention relates to the fields of information retrieval and data mining, and is specifically a time-weighted tripartite news recommendation method, which includes: inputting news data obtained by users, and calculating optimized news resources according to the obtained news data obtained by users value; news recommendation is carried out according to the optimized news resource value; the process of calculating the optimized news resource value includes: using the heat diffusion algorithm to calculate the topic node resource value after the news is transferred to the topic and the news result after the topic is transferred to the news The resource value of the point, using the time weight function to fuse the two resource values, to obtain the optimized news resource value; the present invention uses the time weight function to optimize the news resource value in the news recommendation scene, and solves the problem of edge-related problems in the three-part graph technology. The weight affects the recommendation effect and improves the accuracy of the recommendation results.
Description
technical field [0001] The invention relates to the fields of information retrieval and data mining, in particular to a time-weighted three-part graph news recommendation method. Background technique [0002] With the rapid development of mobile networks and the popularization of smart phones, people's various living habits are also being subtly changed. In the past, news information was mostly obtained by reading newspapers and watching TV. In this way, from the generation of news information to the production of the news to the distribution, it can finally be spread to everyone. The period of time experienced is relatively long, and one of the unique characteristics of news itself is timeliness. If it is not spread within a certain period of time, the news will lose its value and become meaningless. Nowadays, with the emergence of various news clients, browsing news anytime, anywhere has become one of people's daily activities. At the same time, the cost and time of prod...
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IPC IPC(8): G06F16/335G06F16/31G06F16/9536
CPCG06F16/335G06F16/313G06F16/319G06F16/9536
Inventor 韦世红李交泰石旭
Owner CHONGQING UNIV OF POSTS & TELECOMM