Introducing Primer Engines

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06

Topic Modeling

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.

Documentation

VIEW IN API DOCS

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

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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