Pith. sign in

REVIEW 1 cited by

Auctus: A Dataset Search Engine for Data Augmentation

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2102.05716 v2 pith:EOMAVV5H submitted 2021-02-10 cs.IR cs.DB

classification cs.IRcs.DB
keywords dataauctussearchaugmentationchallengesdatasetenginemany
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

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.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Rethinking Dataset Discovery with DataScout

    cs.HC 2025-07 conditional novelty 6.0 of 10

    A dataset search interface with LLM-generated query reformulations, semantic column and granularity filters, and task-specific relevance indicators that helped 12 study participants explore and make sense of dataset s...

Pith tools