Abstract: Provided are a computer program product, system, and method for determining tags to recommend for a document. A natural language processing module determines a document keyword for a document. A tag database search module determines, a tag in a tag database associated with the document keyword. A domain specific search module determines a domain specific tag in a domain specific knowledge base associated with the document keyword. A recommendation is made of at least one of the tag and the domain specific tag as a recommended tag for the document.

Abstract: Metadata is managed for different distributed federated workspaces. A distributed metadata infrastructure is provided for supporting at least two different distributed federated workspaces. The distributed metadata infrastructure monitors the at least two different distributed federated workspaces to identify common metadata between the at least two different distributed federated workspaces. The distributed metadata infrastructure presents a consistent view of the common metadata.

Abstract: Metadata is managed for different distributed federated workspaces. A distributed metadata infrastructure is provided for supporting at least two different distributed federated workspaces. The distributed metadata infrastructure monitors the at least two different distributed federated workspaces to identify common metadata between the at least two different distributed federated workspaces. The distributed metadata infrastructure presents a consistent view of the common metadata.

Abstract: Provided are a method, a system, and a computer program for managing metadata for different distributed federated workspaces. A distributed metadata infrastructure is provided for supporting at least two different distributed federated workspaces. The distributed metadata infrastructure monitors the at least two different distributed federated workspaces to identify common metadata between the at least two different distributed federated workspaces. The distributed metadata infrastructure presents a consistent view of the common metadata.

Abstract: Provided are a method, a system, and a computer program for managing metadata for different distributed federated workspaces. A distributed metadata infrastructure is provided for supporting at least two different distributed federated workspaces. The distributed metadata infrastructure monitors the at least two different distributed federated workspaces to identify common metadata between the at least two different distributed federated workspaces. The distributed metadata infrastructure presents a consistent view of the common metadata.

Abstract: Techniques are described for refining the manual classification of assets classified or categorized using the terms of a business glossary. A semantic refinement mechanism is used to refine the manual classification of such assets, as well as subsequently evaluate the refined asset classifications. Further, the refined asset classifications may be used as a training set for a machine learning classifier. That is, should the classification of an asset contributing to a refinement change, the refinement based on that classification may be undone, at least in some cases.

Abstract: Techniques are described for refining the manual classification of assets classified or categorized using the terms of a business glossary. A semantic refinement mechanism is used to refine the manual classification of such assets, as well as subsequently evaluate the refined asset classifications. Further, the refined asset classifications may be used as a training set for a machine learning classifier. That is, should the classification of an asset contributing to a refinement change, the refinement based on that classification may be undone, at least in some cases.

Abstract: Techniques are described for refining the manual classification of assets classified or categorized using the terms of a business glossary. A semantic refinement mechanism is used to refine the manual classification of such assets, as well as subsequently evaluate the refined asset classifications. Further, the refined asset classifications may be used as a training set for a machine learning classifier. That is, should the classification of an asset contributing to a refinement change, the refinement based on that classification may be undone, at least in some cases.

Abstract: Techniques are described for refining the manual classification of assets classified or categorized using the terms of a business glossary. A semantic refinement mechanism is used to refine the manual classification of such assets, as well as subsequently evaluate the refined asset classifications. Further, the refined asset classifications may be used as a training set for a machine learning classifier. That is, should the classification of an asset contributing to a refinement change, the refinement based on that classification may be undone, at least in some cases.

Abstract: A system and method to support runtime model extension in an Object Relational Mapping (ORM) System. The system includes a relational data storage subsystem for storing and retrieving objects in form of relational data, a tuple storage subsystem for storing and retrieving objects in form of tuple, and a dispatcher/assembler for storing and retrieving original part and extended part of the object respectively into/from the relational data storage subsystem and the tuple storage subsystem. Thus, model extension can be carried out dynamically in the runtime of the ORM system without modifying schema and migrating data in the relational database.