Chris Marokov-
Office of Management and Budget, Executive Office of the President
Title: From Natural Language Processing and Graph Data Models to Knowledge Graphs
Title: From Natural Language Processing and Graph Data Models to Knowledge Graphs
Abstract:
Abstract:
The presentation will demonstrate natural language processing, using IN-SPIRE software (https://in-spire.pnnl.gov/) to harvest and process large amount of text documents. Different visualization of textual data will then help introduce the concept of graph data models as inherent to text from parsing to retrieval. The focus will then turn to network analysis and reveal why any large amalgamation of unstructured and semi-structured data can be efficiently leveraged and analyzed side by side in a graph/network environment. Finally, the presenter will introduce the novel idea of Knowledge Graphs by describing their structural elements and offering examples of their successful application in different domains.
The presentation will demonstrate natural language processing, using IN-SPIRE software (https://in-spire.pnnl.gov/) to harvest and process large amount of text documents. Different visualization of textual data will then help introduce the concept of graph data models as inherent to text from parsing to retrieval. The focus will then turn to network analysis and reveal why any large amalgamation of unstructured and semi-structured data can be efficiently leveraged and analyzed side by side in a graph/network environment. Finally, the presenter will introduce the novel idea of Knowledge Graphs by describing their structural elements and offering examples of their successful application in different domains.