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Chemistry documents semantics by Redfield

Workflow

Knowledge graph from domain specific documents by Redfield

This workflow demonstrates how the knowledge graph might be build to work with domain specific documents. The techniques used for building graph are NER and topic modelling. Neo4j database is used for creating a semantics graph. The workflow is built as an intercative web application, where user may do selection for the named entities and tagged documents related to them.

neo4jtext processingtopic modellingNERRedfieldgraph
Data visualization Text processing and topic modelling Populating the databases Reading the input documents 5 topicsDoc2TopicProcessing documentsbefore LDADocument propertiesScraped documentsTagged documents Documents andtheir properties Topic Extractor(Parallel LDA) Populating graphwith documents GroupBy Populating graphwith tags Populating graphwith topic modeling Populating SQLitewith tagged texts Selecteddocument view Document selector Topic processing Text processing Table Reader Table Reader Table Reader Document processing NE selector Neo4j credentials Data visualization Text processing and topic modelling Populating the databases Reading the input documents 5 topicsDoc2TopicProcessing documentsbefore LDADocument propertiesScraped documentsTagged documents Documents andtheir properties Topic Extractor(Parallel LDA) Populating graphwith documents GroupBy Populating graphwith tags Populating graphwith topic modeling Populating SQLitewith tagged texts Selecteddocument view Document selector Topic processing Text processing Table Reader Table Reader Table Reader Document processing NE selector Neo4j credentials

Download

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Nodes

Chemistry documents semantics by Redfield consists of the following 170 nodes(s):

Plugins

Chemistry documents semantics by Redfield contains nodes provided by the following 12 plugin(s):