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# News Segmentation Results

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:

- `storyText` contains 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.
- `score` is an integer from 0 to 100 that indicates the consistency between the terms in each segment that makes up the `storyText`.
- each `terms/term/text` element contains a key term extracted from the text.
- each `terms/term/weight` element 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.
- the `type` element specifies whether the news segmentation task has classified the segment as a `Story`, `Short Story`, or a segment with `No topic`.

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