Abstract Knowledge graphs contain knowledge about the world and provide a structured
representation of this knowledge. Current knowledge graphs contain only a small subset of …

Rapid progress in machine learning and artificial intelligence (AI) has brought increasing
attention to the potential impacts of AI technologies on society. In this paper we discuss one …

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 …

This is an overview of the end-to-end data cleaning process. Data quality is one of the most
important problems in data management, since dirty data often leads to inaccurate data …

Large labeled training sets are the critical building blocks of supervised learning methods
and are key enablers of deep learning techniques. For some applications, creating labeled …

We introduce HoloClean, a framework for holistic data repairing driven by probabilistic
inference. HoloClean unifies existing qualitative data repairing approaches, which rely on …

A long standing goal of the data management community is to develop general, automated
systems that ingest semi-structured documents and output queryable tables without human …

This article provides a comprehensive overview of the broad area of semantic search on text
and knowledge bases. In a nutshell, semantic search is “search with meaning”. This …