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Article summary:
1. A hierarchical news video semantic index structure is proposed to construct a retrieval and analysis system model based on news video semantics.
2. Various modules are set up for information collection, boundary detection, key frame marking and extraction, semantic indexing, and determining the relationship between each frame and dynamic key frames.
3. Key information recognition and extraction of news video images, voice, and subtitles is completed.
Article analysis:
The article provides a detailed overview of the research conducted on the design of a news video retrieval system based on semantics. The authors have provided an in-depth description of the various components that make up the system such as the index module, retrieval module, database module, text information, motion frame information, time information etc., which makes it easy to understand how the system works. The article also provides a clear explanation of how these components work together to achieve its goal of recognizing and extracting key information from news videos.
The trustworthiness and reliability of this article can be assessed by looking at its sources of information. The authors have cited several relevant sources such as research papers and articles related to their topic which adds credibility to their claims. Additionally, they have provided evidence for their claims in the form of diagrams which further strengthens their argument.
However, there are some areas where this article could be improved upon. For example, while it does provide an overview of how the system works in theory, it does not provide any practical examples or case studies that demonstrate its effectiveness in real-world scenarios. Additionally, there is no discussion about potential risks associated with using this system or any counterarguments that could be made against it which would help readers gain a better understanding of its limitations and drawbacks.