The vector database market is experiencing rapid growth, with projections estimating it will reach $10.6 billion by 2032, ...

Subsequently, we leverage the valuable factual evidence among real-world entities, which is enclosed in two open-source knowledge graphs (Wikidata and DBpedia), and augment the heterogeneous graph ...

Knowledge graphs (KGs) are the foundation of artificial intelligence applications but are incomplete and sparse, affecting their effectiveness. Well-established KGs such as DBpedia and Wikidata lack ...

Early works such as the development of DBpedia highlighted the utility of LLMs in pretraining ... Through this approach, a more accessible and scalable solution for generating meaningful knowledge ...

Knowledge graphs have existed for a long time and have proven valuable across social media sites, cultural heritage institutions, and other enterprises. A knowledge graph is a collection of ...

They require a knowledge graph. How does the journey to a knowledge graph start with unstructured data—such as text, images, and other media? The evolution of web search engines offers an ...

DBpedia, for instance, contains about 900 million triples ... from dataset preparation and disambiguation to knowledge graph querying, data processing, and representation learning. Integrating LLM ...

Knowledge graphs are vital for answering complex relational queries ... including authoritative sources like DBPedia and Wikidata, web-based texts, and synthetically generated datasets. This eclectic ...