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 ...

In the age when data is everything to a business, managers and analysts alike are looking to emerging forms of databases to paint a clear picture of how data is delivering to their businesses. The ...

What if you could transform vast amounts of unstructured text into a living, breathing map of knowledge—one that not only organizes information but reveals hidden connections you never knew existed?

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 ...

生成AI、なかでもRAGの分野で「Knowledge Graph」の注目が高まっている。文書などを構造化することで、生成AIの知識として利用する方法だ。 ベクトル検索方式のRAGと異なり、情報の関係を定義することで、より正確な回答が得られる場合があるのが特徴だ。

What if you could transform overwhelming, disconnected datasets into a living, breathing map of relationships, one that not only organizes your data but also reveals insights you didn’t even know you ...

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 ...

Google’s Knowledge Graph saw its largest contraction in a decade in June: a two-stage, one-week drop of 6.26% – over 3 billion entities deleted. Since 2015, we’ve tracked the Knowledge Graph and have ...