ninalx/table2vec-lideng

Table2Vec: Neural Word and Entity Embeddings for Table Population and Retrieval

31
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Emerging

This project helps data analysts and researchers find and complete information in large collections of structured tables, such as those found on the web. It takes incomplete tables or search queries as input and outputs relevant tables or missing rows and columns. It's designed for anyone working with extensive tabular data who needs to quickly populate missing information or retrieve related tables.

No commits in the last 6 months.

Use this if you frequently work with large databases of tables and need a way to efficiently find relevant tables or automatically fill in missing data within your existing tables.

Not ideal if your primary need is data entry from unstructured text or if you only work with a small number of carefully curated tables.

data-enrichment information-retrieval knowledge-base-management tabular-data-analysis data-completion
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 17 / 25

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Stars

24

Forks

8

Language

Python

License

Last pushed

Oct 28, 2018

Commits (30d)

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