When organizations conflate data readiness with knowledge readiness, the AI can access the records but not the judgment ...

Wikipedia defines big data as: “Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data ...

For years, the best alternative to a human agent was a chatbot. GenAI, combined with the right large language model and ...

Privacy and security concerns restrict access to original training datasets, posing significant challenges for model compression. Data-Free Knowledge Distillation ...

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Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Birgitta Böckeler, Distinguished Engineer at ...

Metabolite annotation in untargeted metabolomics remains challenging due to the vast structural diversity of metabolites. Network-based approaches have emerged as powerful strategies, particularly for ...

Understand the building blocks of knowledge graphs – entities, relationships and attributes – and how they relate to information retrieval. Knowledge graphs are reshaping how we organize and make ...

A knowledge graph, is a graph that depicts the relationship between real-world entities, such as objects, events, situations, and concepts. This information is typically stored in a graph database and ...

D2K is an exemplar of collaborative cross-disciplinary research in data science and social science related to health and biomedicine. The Data to Knowledge Research Group (D2K) focuses on methods, ...