Network video hotspot event finding method based on multi-source information fusion analysis

Abstract

A network video hotspot event finding method based on multi-source information fusion analysis comprises the steps that 1, multi-source information network videos are acquired; 2, the multi-source information of the network videos is structuralized into descriptive keyword tags; 3, subjective sensitivity parameters of the network videos are obtained according to the matching degree between the network video semantically-structuralized keyword tags obtained in the step 2 and a user-defined sensitive word dictionary; 4, objective hot-degree parameters of the network videos are obtained according to the click rate and time fields of the multi-source information of the network videos; 5, a network video sensitivity prediction model is established according to the subjective sensitivity parameters obtained in the step 3 to predict the subjective sensitivity of new network videos; 6, a network video hot-degree prediction model is established according to the objective hot-degree parameters obtained in the step 4 to predict the objective hot degree of the new network videos; 7, videos with the weighted summation of the subjective sensitivity and the objective hot degree ranking in the top in the network videos are selected as hotspot videos.

Description

technical field [0001] The invention belongs to the field of computer vision and relates to a method for discovering network video hotspot events. Background technique [0002] Network video is an important part of today's information society. Web video is massive and growing rapidly. While bringing convenience to people's lives, detecting and tracking hot and sensitive events from network video is an urgent problem to be solved, regardless of national security or storage convenience. [0003] Existing network video hotspot event discovery schemes usually use manual detection to judge whether a video contains sensitive or hotspot information, or rely on text information such as video tags and comments for judgment. However, on the one hand, with the large-scale increase in the number of videos, using manual detection will consume a lot of manpower and time, resulting in slow response. On the other hand, there are a large number of videos that do not contain complete and a...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problems of large-scale network video and complex semantic content, the present invention develops a network video download technology based on abstract extraction, combines multi-source information such as tags and comments of network video, and develops a technology based on multi-source and multi-dimensional information fusion through concept detection technology. Based on the semantic structuring technology of online video, based on the topic model, the automatic discovery and recommendation technology of video hotspot events was developed, and finally a network video hotspot event discovery method based on multi-source information fusion analysis was proposed. Sensitive event detection function, with great scientific research and economic and social value

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