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The following XML shows a single record produced by news segmentation.
<NewsSegmentationResult> <id>af4475f5-beb2-401e-bf73-fb494f63af27</id> <storyText>business secretary says the government will consider co investing with a Buy on commercial terms <SIL> ...</storyText> <score>0</score> <terms> <term> <text>Buy</text> <weight>170</weight> </term> <term> <text>business secretary says</text> <weight>120</weight> </term> <term> <text>consider co investing</text> <weight>110</weight> </term> <term> <text>commercial terms</text> <weight>90</weight> </term> ... </terms> <type>Short story</type> </NewsSegmentationResult>
The record contains the following elements:
storyTextcontains the text extracted from the video. The text is extracted from the audio by speech-to-text. Words are then combined into segments by the text segmentation task. News Segmentation analyzes the segments and combines one or more segments into a result that represents a story, short story, or video with no topic.
scoreis an integer from 0 to 100 that indicates the consistency between the terms in each segment that makes up the
terms/term/textelement contains a key term extracted from the text.
terms/term/weightelement contains the weight of the associated term. You might want to use this weight when building a term cloud. The weights are relative to the other terms in the story, and cannot be compared across stories.
typeelement specifies whether the news segmentation task has classified the segment as a
Short Story, or a segment with