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Table understanding approaches for extracting knowledge from heterogeneous tables
Author(s) -
Bonfitto Sara,
Casiraghi Elena,
Mesiti Marco
Publication year - 2021
Publication title -
wiley interdisciplinary reviews: data mining and knowledge discovery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.506
H-Index - 47
eISSN - 1942-4795
pISSN - 1942-4787
DOI - 10.1002/widm.1407
Subject(s) - table (database) , computer science , exploit , cluster analysis , information retrieval , data mining , data science , knowledge base , transformation (genetics) , knowledge extraction , preprocessor , data pre processing , world wide web , artificial intelligence , biochemistry , chemistry , computer security , gene
Table understanding methods extract, transform, and interpret the information contained in tabular data embedded in documents/files of different formats. Such automatic understanding would allow to exploit tabular information with the aim of accurately answering queries, or integrating heterogeneous repositories of information in a common knowledge base, or exchanging information among different sources. The purpose of this survey is to provide a comprehensive analysis of the research efforts so far devoted to the problem of table understanding and to describe systems that support the transformation of heterogeneous tables into meaningful information. This article is categorized under: Application Areas > Data Mining Software Tools Technologies > Data Preprocessing Technologies > Structure Discovery and Clustering