MC Miner™ is an integrated, cross talking, multi-component solution for content ingestion, enrichment and exchange including;
- A parser to ingest various forms of inputs (structured and unstructured)
- Entity Recognition module to Identify different categories of named entities
- Ontologies/CVs of named entities (Authors, Topics, Institutions, Places etc., With standardizations)
- An AI based clustering algorithm for automated clustering of similar named entities
- ML rule based engine to influence the said clustering via plug and play user inputs
- Optional component allowing for manual intervention to disambiguate semi-automated data points
- Entity centric recommendations and similarity suggestions on the content
- APIs to the access the linked data store consisting of the disambiguated and standardized entities from all/any of the above workflow components
Applications
Context aware and entity centric summarizations. For instance, this engine can address use cases like identifying content specifically centered around evidence based treatments for a specific disease. Create building blocks for a semantic data lake and knowledge discovery solutions Data repurposing like collection creations Content recommendations tailored for user engagement, discovery led content consumptions etc., Interested in MC Miner™ ?
