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arXiv · 2411.11891

Survey on Semantic Interpretation of Tabular Data: Challenges and Directions

Marco Cremaschi·Blerina Spahiu·Matteo Palmonari·Ernesto Jimenez-Ruiz
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Abstract

Tabular data plays a pivotal role in various fields, making it a popular format for data manipulation and exchange, particularly on the web. The interpretation, extraction, and processing of tabular information are invaluable for knowledge-intensive applications. Notably, significant efforts have been invested in annotating tabular data with ontologies and entities from background knowledge graphs, a process known as Semantic Table Interpretation (STI). STI automation aids in building knowledge graphs, enriching data, and enhancing web-based question answering. This survey aims to provide a comprehensive overview of the STI landscape. It starts by categorizing approaches using a taxonomy of 31 attributes, allowing for comparisons and evaluations. It also examines available tools, assessing them based on 12 criteria. Furthermore, the survey offers an in-depth analysis of the Gold Standards used for evaluating STI approaches. Finally, it provides practical guidance to help end-users choose the most suitable approach for their specific tasks while also discussing unresolved issues and suggesting potential future research directions.

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Marco Cremaschi, Blerina Spahiu, Matteo Palmonari, Ernesto Jimenez-Ruiz. 2024-11-07. Survey on Semantic Interpretation of Tabular Data: Challenges and Directions. https://arxiv.org/abs/2411.11891

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