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Popular use cases for graph data #49
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Cross linking semantalytics/awesome-semantic-web#32 |
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http://sps.columbia.edu/executive-education/knowledge-graph-conference https://www.eventbrite.com/e/2019-knowledge-graph-conference-tickets-54867900367 Knowlede Graphs everywhere:
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I would like to learn more about the difference between neo4j and other knowledge graph platforms such as ontotext. I work specifically in clinical natural language processing but leverage various clinical ontologies. hWhat is the difference between the formats and can both provide semantic relationships? |
Could you be more precise what you mean with all these use cases? Many of the given use cases are buzzwords or don't say anything. For instance, "Sensors" is not a use case. At best it describes an area of expertise which contains hardware and software. Or "Network and database monitoring": Does RDF provide network monitoring now? I might anticipate what you mean with all these terms, but I am looking forward to a more detailed explanation of the terms used. |
The aim of making RDF easier for the next 33% of developers begs the question of what are the popular application use cases for graph data (as a generalisation of RDF)? Here are some examples taken from graph database vendor websites.
Neo4J:
• Recommendation engines for e-commerce
• Network and database monitoring
• Fraud detection and analytics
• Social media and social networks
• Knowledge graphs for enhanced search services
• Identity and access management
• Privacy, risk and compliance
• Master data management
• Artificial Intelligence and analytics
Amazon Neptune:
• Network/IT operations
• Social networking
• Recommendation engines
• Fraud detection
• Knowledge graphs
• Life sciences
I am sure that this is just a few examples from a much much larger set. How can we reach out and gather information on use cases across different sectors, and the associated challenges facing application developers where new standards would help?
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