information analyst

In general, the REST Client API calls out a GATE-based annotation pipeline and sends back enriched data in RDF form. Organizations typically customize these pipelines which consist of any GATE-developed set of text mining algorithms for scoring, machine learning, disambiguation or any of the other wide range of text mining techniques.

It is important to note that these text mining pipelines create RDF in a linear fashion and feed GraphDB™. Once the RDF is enriched in this fashion and stored in the database, these annotations can then be modified, edited or removed. This is particularly useful when integrating with Linked Open Data (LOD) sources. Updates to the database are populated automatically when the source information changes.

For example, let’s say your text mining pipeline is referencing Freebase as its Linked Open Data source for organization names. If an organization name changes or a new subsidiary is announced in Freebase, this information will be updated as reference-able metadata in GraphDB™.

In addition, this tightly-coupled integration includes a suite of enterprise-grade APIs, the core of which is the Concept Extraction API. This API consists of a Coordinator and Entity Update Feed. Here’s what they do:

• The Concept Extraction API Coordinator module accepts annotation requests and dispatches them towards a group of Concept Extraction Workers. The Coordinator communicates with GraphDB™ in order to track changes leading to updates in each worker’s entity extractor. The API Coordinator acts as a traffic cop allowing for approved and unique entities to be inserted in GraphDB™ while preventing duplicates from taking up valuable real estate.
• The Entity Update Feed (EUF) plugin is responsible for tracking and reporting on updates about every entity (concept) within the database that has been modified in any way (added, removed, or edited). This information is stored in the graph database and query-able via SPARQL. Reports can be run notifying a user of any and all changes.

Other APIs include Document Classification, Disambiguation, Machine Learning, Sentiment Analysis & Relation Extraction. Together, this complete set of technology allows for tight integration and accurate processing of text while efficiently storing resulting RDF statements in GraphDB™.

As mentioned, the value of this tightly-coupled integration is in the rich metadata and relationships which can now be derived from the underlying RDF database. It’s this metadata that powers high performance search and discovery or website applications – results are compete, accurate and instantaneous.

In general, the REST Client API calls out a GATE-based annotation pipeline and sends back enriched data in RDF form. Organizations typically customize these pipelines which consist of any GATE-developed set of text mining algorithms for scoring, machine learning, disambiguation or any of the other wide range of text mining techniques.

It is important to note that these text mining pipelines create RDF in a linear fashion and feed GraphDB™. Once the RDF is enriched in this fashion and stored in the database, these annotations can then be modified, edited or removed. This is particularly useful when integrating with Linked Open Data (LOD) sources. Updates to the database are populated automatically when the source information changes.

For example, let’s say your text mining pipeline is referencing Freebase as its Linked Open Data source for organization names. If an organization name changes or a new subsidiary is announced in Freebase, this information will be updated as reference-able metadata in GraphDB™.

In addition, this tightly-coupled integration includes a suite of enterprise-grade APIs, the core of which is the Concept Extraction API. This API consists of a Coordinator and Entity Update Feed. Here’s what they do:

• The Concept Extraction API Coordinator module accepts annotation requests and dispatches them towards a group of Concept Extraction Workers. The Coordinator communicates with GraphDB™ in order to track changes leading to updates in each worker’s entity extractor. The API Coordinator acts as a traffic cop allowing for approved and unique entities to be inserted in GraphDB™ while preventing duplicates from taking up valuable real estate.
• The Entity Update Feed (EUF) plugin is responsible for tracking and reporting on updates about every entity (concept) within the database that has been modified in any way (added, removed, or edited). This information is stored in the graph database and query-able via SPARQL. Reports can be run notifying a user of any and all changes.

Other APIs include Document Classification, Disambiguation, Machine Learning, Sentiment Analysis & Relation Extraction. Together, this complete set of technology allows for tight integration and accurate processing of text while efficiently storing resulting RDF statements in GraphDB™.

As mentioned, the value of this tightly-coupled integration is in the rich metadata and relationships which can now be derived from the underlying RDF database. It’s this metadata that powers high performance search and discovery or website applications – results are compete, accurate and instantaneous.