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Neo4j Live: Building a Semantics-Based Recommender System for ESG Documents
Knowledge Graphs have become increasingly important for knowledge representation and data consolidation in enterprises. They provide the basis to solve complex data problems, provide insights into data and thereby support intelligent decision making at the digital workplace.
In this talk, we present an approach to bring together Semantic Web technologies and Neo4j to build a knowledge-based recommender that is powered by a semantic knowledge graph and processes the recommendations using a property graph representation.
We present the use case of analysing ESG-related documents and supporting the writing of ESG reports by providing intelligent insights into ESG standards and documents.
Guest: Astrid Krickl
Data & Knowledge Engineer, Semantic Web Company
Astrid is working at Semantic Web Company since very recently, November 2022 as a Data and Knowledge Engineer. She studied business informatics at UAS Technikum Vienna and worked already as software developer and tester, and later as system engineer at WU Vienna. She also has research experience as she worked as a research and teaching associate at WU Vienna. There she investigated in tools and techniques (mainly NLP and machine learning) that can help with the problem of misinformation and fake news.
In this talk, we present an approach to bring together Semantic Web technologies and Neo4j to build a knowledge-based recommender that is powered by a semantic knowledge graph and processes the recommendations using a property graph representation.
We present the use case of analysing ESG-related documents and supporting the writing of ESG reports by providing intelligent insights into ESG standards and documents.
Guest: Astrid Krickl
Data & Knowledge Engineer, Semantic Web Company
Astrid is working at Semantic Web Company since very recently, November 2022 as a Data and Knowledge Engineer. She studied business informatics at UAS Technikum Vienna and worked already as software developer and tester, and later as system engineer at WU Vienna. She also has research experience as she worked as a research and teaching associate at WU Vienna. There she investigated in tools and techniques (mainly NLP and machine learning) that can help with the problem of misinformation and fake news.