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 ...

Semantic Table Interpretation is a critical process that transforms tabular data into rich, machine-readable semantic representations by associating table elements with concepts from established ...

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.

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 ...

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 ...

Without structured context, GenAI applications are noisy and error prone. After all, real intelligence requires context, precision and understanding. This is why ...

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 ...

Modern consumers expect personalized experiences tailored to their unique preferences, behaviors and needs. Businesses striving to meet these expectations are turning to AI-powered knowledge graphs — ...