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 ...

The concept of knowledge graphs arose from scientific advances in a variety of research fields, including the semantic web, databases, natural language processing, and machine learning. According to ...

インターネット検索や機械学習に欠かせないナレッジグラフは、グラフ構造でさまざまな知識を連結し、データを連係させて知識の探索や高度な分析を実行することができます。情報分野の学術雑誌「Communications of the ACM」が、人工知能と機械学習のベースと ...

Knowledge graphs and ontologies form the backbone of the Semantic Web by enabling the structured representation and interconnection of data across diverse domains. These frameworks allow for the ...

Text mining and knowledge graphs connect cell-culture parameters to glycosylation for faster bioprocess optimization.

Ever since the introduction of the Google Knowledge Graph, a growing number of organizations have adopted this powerful technology to drive efficiency and effectiveness in their data management.

For decades, enterprise data infrastructure focused on answering the question: “What happened in our business?” Business intelligence tools, data warehouses, and pipelines were built to surface ...

While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...