Knowledge Factory

Improve ROI from third-party data

Knowledge Factory is a set of metadata handling tools, a Workflow Manager and an advanced Knowledge Graph that maximize the value of data sources. The metadata tools control the ingestion, mash-up, reconciliation and de-duplication of data from multiple commercial and free data providers, like Gracenote, TMDb and Wikidata.

Knowledge Factory reduces the editorial overhead on data quality by selectively focusing on human intervention only when strictly needed, maximizing the value of the aggregate available data sources by uncovering hidden relationships between content, while also optimizing ROI from third-party data licensing contracts.

Code-less visual Workflow Manager enables administrators to reconfigure existing metadata processing “recipes” and create new ones while the Knowledge Graph maximizes third party data sources to infer missing metadata and provides unprecedented depth of information about content items.

Features

Metadata Ingestion & Enrichment

Maximize the value of the aggregate available data sources

ContentWise Knowledge Factory ingests CMS-provided metadata and enriches it with external public and private data sources to create deeper and more contextually relevant information related to each asset in your content catalog.

The Knowledge Factory automatically reconciles VOD and EPG information as well as syndicated data from multiple sources (like Gracenote, TMDb and Wikidata). ContentWise supports out-of-the-box adapters for widely used metadata formats for automatic ingestion such as Tribune TMS, CableLabs ADI 1.0 and 2.x, XMLTV, TvAnytime and more. Any other type of format (csv, xml, etc) and ingestion mechanism (SQL Query, webservices call, etc…) is also supported.

Knowledge Graph

Intelligently match viewers interest patterns with content

Knowledge Factory enables Social TV applications, by matching movies, series and actors within users preferences.

ContentWise Knowledge Factory enables operators to get insights on each individual users preferences patterns and relate them to content metadata, leveraging the power of a complete knowledge graph. The knowledge graph allows to create a much more contextual and intimately personalized discovery and search experience.