Large-scale data analytics using statistical machine learning (ML), popularly called
advanced analytics, underpins many modern data-driven applications. The data …

Large language models (LLMs), such as GPT-4, are revolutionizing software's ability to
understand, process, and synthesize language. The authors of this paper believe that this …

Big data management for information centralization (ie making data of interest findable) and
integration (ie making related data connectable) in health research is a defining challenge in …

With the extensive growth of data that has been joined with the thriving development of the
Internet in this century, finding or getting valuable information and knowledge from these …

The field of data integration has expanded significantly over the years, from providing a
uniform query and update interface to structured databases within an enterprise to the ability …

Can one build a knowledge graph (KG) for all products in the world? Knowledge graphs
have firmly established themselves as valuable sources of information for search and …

Machine learning (ML) has widespread applications and has revolutionized many
industries, but suffers from several challenges. First, sufficient high-quality training data is …

Most existing knowledge graphs (KGs) in academic domains suffer from problems of
insufficient multi-relational information, name ambiguity and improper data format for large …

We introduce Saga, a next-generation knowledge construction and serving platform for
powering knowledge-based applications at industrial scale. Saga follows a hybrid batch …

End-to-end AutoML has attracted intensive interests from both academia and industry which
automatically searches for ML pipelines in a space induced by feature engineering …