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Resources - NLP
Videos, Slides, Case Studies and other GraphAware related resources
Knowledge Graphs Powered By NLP and Network Science
Vlasta Kůs takes us through converting a corpus of research papers through Natural Language Processing, entity (relation) extraction and graph algorithms to highly informative connected insights organized in a knowledge graph.
Improving Information Retrieval with Knowledge Graphs and Natural Language Processing
Christophe Willemsen, CTO, GraphAware, explains how to apply NLP to extract entities and key phrases to build and search knowledge graphs
Connect, Enrich, Evolve: Convert Unstructured Data Silos to Knowledge Graphs
Dr. Alessandro Negro, Chief Scientist at GraphAware, presents on knowledge graphs at GraphTour DC.
Knowledge Graphs and Chatbots with Neo4j and Amazon Alexa
Knowledge Graphs are becoming the de-facto solution for managing complex aggregated knowledge, and Neo4j is the leading platform for storing and querying connected data. In this talk, Christophe will describe a graph-centric cognitive computing pipeline and detail the process from the ingestion of unstructured text up to the generation of a knowledge graph, queryable using natural language through chatbots built with IBM Watson Conversation.
Knowledge Graphs and Chatbots with Neo4j and IBM Watson
In this talk, Christophe will describe a graph-centric cognitive computing pipeline and detail the process from the ingestion of unstructured text up to the generation of a knowledge graph, queryable using natural language through chatbots built with IBM Watson Conversation.
Taming text with Neo4j: The Graphaware NLP Framework
A great part of the world’s knowledge is stored using text in natural language, but using it in an effective way is still a major challenge. Natural Language Processing (NLP) techniques provide the basis for harnessing this huge amount of data and converting it into a useful source of knowledge for further processing. By Alessandro Negro, Chief Scientist, GraphAware.