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Enrich Open Measures Odnoklassniki with Datastreamer Cultural Reference Recognition Model
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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.
About Datastreamer Cultural Reference Recognition Model
Movies, songs, memes, books, and other cultural references can be detected with this LLM-powered model 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.
Quickly enrich Open Measures Odnoklassniki with Datastreamer Cultural Reference Recognition Model with a Datstreamer Pipeline.
Step 1
Start your Pipeline with Open Measures Odnoklassniki
Web data is an essential component of enterprise data pipelines, enabling organizations to integrate structured and unstructured data from partner APIs, legacy systems, and public web sources.
Step 2
Add Datastreamer Cultural Reference Recognition Model to enrich
Boost your web data capabilities by applying a wide range of operations—enrich, augment, join, structure, filter, store, search, and more. With Datastreamer, you get access to hundreds of plug-and-play tools to power your workflows.
Step 3
That's it! You have just connected Open Measures Odnoklassniki and Datastreamer Cultural Reference Recognition Model
Datastreamer makes working with web data simpler than ever. Easily enhance your Pipelines with new features and finally eliminate the operational roadblocks that once held you back.