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Tuesday, April 21 • 4:40pm - 4:55pm
Resolving Locations in Text with NLP and Neo4j

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Humans are very good at inferring the location of events described in text, even when no places are mentioned by name. Can computers do something similar? We demonstrate a solution, using a combination of natural language processing and graph techniques applied to a corpus of online news stories.

Effective news monitoring, for competitive intelligence and other purposes, often requires an understanding of the location at which the events mentioned in an article occur. This information is sometimes not given explicitly in the text, but can be inferred using a combination of natural language processing and graph techniques. This talk describes a Neo4j-based system for performing this task. We also discuss some lessons learned along the way, and a graph-based approach to enhancing the traditional process of named entity recognition.

avatar for Stephen Hall

Stephen Hall

Software Engineer, Predix Communications
After receiving a PhD in Electronic and Computer Engineering from the University of Wollongong, Australia, I held various academic and industry positions in telecommunications and computing. In 2000, I co-founded Predix Communications in Cape Town, South Africa, and the company developed... Read More →

Tuesday April 21, 2020 4:40pm - 4:55pm EDT
Room 6