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Apply Datastreamer Emotion Detection Classifier to Open Measures Odnoklassniki
Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
About Datastreamer Emotion Detection Classifier
Detect emotion within content, such as fear, happiness, sadness, disgust, etc. It is able to process content in over 200+ languages. This classifier can instantly consume the content within a pipeline, optimize the content for speed and cost efficiency, and pass into LLM systems. Within the classifier, the LLM response is restructured, the post is augmented with the new metadata, and continues in the pipeline.
About Open Measures Odnoklassniki
Open Measures collection on OK(Odnoklassniki) began by aggregating around 5,000 OK group URLs that appeared across the existing collections and fed these into the crawler. The crawler then spiders across these groups by collecting posts, comments and group members.
Quickly apply Datastreamer Emotion Detection Classifier to Open Measures Odnoklassniki with a Datstreamer Pipeline.
Step 1
Start your Pipeline with Open Measures Odnoklassniki
Enterprise data pipelines are built on the continuous flow of web data, which can originate from partner networks, internal infrastructures, or any external digital source.
Step 2
Add Datastreamer Emotion Detection Classifier with an Operation
Datastreamer lets you accelerate your data usage by applying operations like structuring, enriching, joining, and filtering—choose from hundreds of prebuilt, plug-and-play options.
Step 3
That's it! You have just connected Datastreamer Emotion Detection Classifier and Open Measures Odnoklassniki
Supercharge your data workflows with Datastreamer. Add flexibility to your Pipelines and put an end to the common bottlenecks in handling web data.