Topic Modeling

Identify the topic that the text is talking about without the need for training data or an ontology, or integrate the engine with your own ontology.

The Topics-Abstractive engine can be trained to generate abstractive topic labels for a single document which include new words or phrases that may or may not be contained in the source data, whereas the Topics-Extractive engine generates the topics in the document, which only includes words or phrases that were contained in the source data.

  • Example

    An elaborate plan to reveal a baby’s gender went disastrously wrong when a “smoke-generating pyrotechnic device” ignited a wildfire that consumed thousands of acres east of Los Angeles over Labor Day weekend, the authorities said.

    A firefighter died on Sept. 17 battling the blaze — labeled the El Dorado Fire — in the San Bernardino National Forest, the U.S. Forest Service said.

    Identified Topics

    [01]

    Wildfires

    [02]

    Gender Reveal Parties

    [03]

    El Dorado Fire

Available Engines

  • Topics – Abstractive
  • Topics – Extractive

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