Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/63871

A Qualitative Literature Review on Linkage Techniques for Data Integration

File Size Format  
0106.pdf 244.79 kB Adobe PDF View/Open

Item Summary

Title:A Qualitative Literature Review on Linkage Techniques for Data Integration
Authors:Kruse, Felix
Hassan, Ahmad Pajam
Awick, Jan-Philipp
Marx Gómez, Jorge
Keywords:Data, Text, and Web Mining for Business Analytics
big data integration
data science
entity linking
linkage techniques
show 1 morerecord linkage
show less
Date Issued:07 Jan 2020
Abstract:The data linkage techniques ”entity linking” and ”record linkage” get rising attention as they enable the integration of multiple data sources for data, web, and text mining approaches. This has resulted in the development of numerous algorithms and systems for these techniques in recent years. The goal of this publication is to provide an overview of these numerous data linkage techniques. Most papers deal with record linkage and structured data. Processing unstructured data through entity linking is rising attention with the trend Big Data. Currently, deep learning algorithms are being explored for both linkage techniques. Most publications focus their research on a single process step or the entire process of ”entity linking” or ”record linkage”. However, the papers have the limitation that the used approaches and techniques have always been optimized for only a few data sources.
Pages/Duration:11 pages
URI:http://hdl.handle.net/10125/63871
ISBN:978-0-9981331-3-3
DOI:10.24251/HICSS.2020.132
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Data, Text, and Web Mining for Business Analytics


Please email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.

This item is licensed under a Creative Commons License Creative Commons