Media Server 25.3
Media Server Help

# 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`.

Copyright 2025 Open Text
Version 25.3 | Last updated July 2025

Send documentation feedback

Close

Send documentation feedback

To send feedback using your default email client, open an email window.

Otherwise, send your feedback and the information below to MFI-swpdl.idoldocsfeedback@opentext.com.

We appreciate your feedback!

Product: Knowledge Discovery Media Server 25.3

Topic Title: News Segmentation Results