2021/02/10 by Sonia Castelo, Rémi Rampin, Castelo, Sonia +9 · 7 citations
Computer Science · Decision Sciences · #Data Quality and Management #Data Stream Mining Techniques #Databases (cs.DB) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Web Data Mining and Analysis
paper · pdf · doi:10.48550/arxiv.2102.05716
openalex publication_date 2021/02/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The large volumes of structured data currently available, from Web tables to open-data portals and enterprise data, open up new opportunities for progress in answering many important scientific, societal, and business questions. However, finding relevant data is difficult. While search engines have addressed this problem for Web documents, there are many new challenges involved in supporting the discovery of structured data. We demonstrate how the Auctus dataset search engine addresses some of these challenges. We describe the system architecture and how users can explore datasets through a rich set of queries. We also present case studies which show how Auctus supports data augmentation to improve machine learning models as well as to enrich analytics.