Topic extraction is very often a crucial step in Natural Language Processing. It results in lists of entities, concepts, phrases, numbers that often are the input for further processes, used for Competitive Intelligence, Social Media Analysis and Search and Content Recommendation. The items that are extracted are very diverse. Often they are also densely connected. These characteristics are in the sweet spot of graph databases, and more precisely in graph databases that use a property graph model, because these offer the possibility to add other that results from post-processing, like similarity coefficients, sentiment scores and user-ratings.
During the meetup , Tom Zeppenfeldt will illustrate how the Graphileon platform can be used to connect various webservices NewsApi, Lateral Article Extractor and MeaningCloud to process articles and use Neo4j's Cypher and graph algorithms to find similarities.
Live Broadcast Date: January 16, 2019