Table understanding approaches for extracting knowledge from heterogeneous tables

Abstract

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

[Retracted] Schema‐Based Mapping Approach for Data Transformation to Enrich Semantic Web

“…It is outdated and hence not supported by most currently available commercial products like Microsoft SQL Server and Oracle. Therefore, it is required to design an efficient query translation model that supports low-end recursion functionality for various products rather than involving only the advanced DBMS features of the most sophisticated systems [27,28]. Secondly, SQL queries through sql'99 recursions generated from the translation algorithms are usually complex in structure and large.…”

Semantic Integration of Heterogeneous and Complex Spreadsheet Tables

“…At current stage, we have started working on a survey on related works in the context of table understanding and semantic interpretation of tables [2]. In this survey, we have outlined the different phases in which the table understanding problem can be organized (localization, segmentation, functional and structural analysis and integration) and presented the main approaches proposed in the last fifteen years.…”

Spread2RML: Constructing Knowledge Graphs by Predicting RML Mappings on Messy Spreadsheets

“…Our research contributes to the discipline of table interpretation in the field of table understanding (for a recent survey see [3]). Interpretation of tables is usually approached by applying schema matching and schema mapping techniques.…”

“…To be able to express RML mappings for spreadsheets, we utilize our previous work [16] and make some assumptions about the sheets' structure and mappings. Regarding [3], we assume that tables in spreadsheets are already correctly localized, segmented and functional as well as structural analyzed. They are expected to have a 1-dimensional vertical layout without nested headers.…”