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How does ModuleQ find recommendations for you?

ModuleQ's content pipeline aggregates about 60K articles daily from Microsoft News and other RSS feeds.

ModuleQ's recommendation system chooses articles for your daily news update from its content pipeline. ModuleQ's content pipeline aggregates about 60K articles daily from Microsoft News and other RSS feeds.

The content pipeline is designed to handle different types of textual content, such as news and research content. It ingests unstructured textual content and analyzes it to generate descriptive semantic metadata about the content. For content analytics, we use Refinitiv's Intelligent Tagging service that is designed for business content, in addition to our own analysis. The pipeline only stores metadata and links to the content, rather than the content item itself. So, recommendations always take you back to content in its original location.

Beyond news, ModuleQ's content pipeline can ingest content and metadata stored in SharePoint and other text document repositories, such as Azure blobs. Untagged content that is sensitive in nature can be annotated with a version of Intelligent Tagging that runs within the organization's own tenant.

Once content metadata has been acquired, it's ready to be considered by ModuleQ's recommendation system. ModuleQ uses your interests and content metadata to score and rank content for your profile. During this pilot, ModuleQ selects 4 articles among the top recommendations for your interests to send in your daily update. The other top recommendations will be visible in the future News tab.