mlsanityData to 7 Oct 2026

Learning Semantic Annotations for Tabular Data

arXiv 1906.00781 ↗First posted 30 May 2019cs.DB cs.IR cs.LGcited by 17

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Abstract (arXiv)

The usefulness of tabular data such as web tables critically depends on understanding their semantics. This study focuses on column type prediction for tables without any meta data. Unlike traditional lexical matching-based methods, we propose a deep prediction model that can fully exploit a table's contextual semantics, including table locality features learned by a Hybrid Neural Network (HNN), and inter-column semantics features learned by a knowledge base (KB) lookup and query answering algorithm.It exhibits good performance not only on individual table sets, but also when transferring from one table set to another.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 May 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 4; 2023: 2; 2024: 3; 2025: 1; 2026: 2.

17 papers.

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  1. 2021SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Trainingcited by 310
  2. 2022Table Pre-training: A Survey on Model Architectures, Pre-training Objectives, and Downstream Taskscited by 42
  3. 2021Annotating Columns with Pre-trained Language Modelscited by 37
  4. 2022PTab: Using the Pre-trained Language Model for Modeling Tabular Datacited by 30
  5. 2021TCN: Table Convolutional Network for Web Table Interpretationcited by 24
  6. 2023ArcheType: A Novel Framework for Open-Source Column Type Annotation using Large Language Modelscited by 15
  7. 2022Table Retrieval May Not Necessitate Table-specific Model Designcited by 11
  8. 2022It's AI Match: A Two-Step Approach for Schema Matching Using Embeddingscited by 4
  9. 2023AdaTyper: Adaptive Semantic Column Type Detectioncited by 4
  10. 2021Generating Table Vector Representationscited by 3
  11. 2024Graph Neural Network Approach to Semantic Type Detection in Tablescited by 3
  12. 2024KGLink: A column type annotation method that combines knowledge graph and pre-trained language modelcited by 3
5 more
  1. 2024Survey on Semantic Interpretation of Tabular Data: Challenges and Directionscited by 3
  2. 2026TabEmb: Joint Semantic-Structure Embedding for Table Annotationcited by 1
  3. 2021Proceedings of the First Workshop on Weakly Supervised Learning (WeaSuL)cited by 0
  4. 2025Conceptual Schema Inference for Tabular Datasets using Large Language Modelscited by 0
  5. 2026ZTab: Domain-based Zero-shot Annotation for Table Columnscited by 0