DocumentCode
3717163
Title
Big data entity resolution: From highly to somehow similar entity descriptions in the Web
Author
Vasilis Efthymiou;Kostas Stefanidis;Vassilis Christophides
Author_Institution
University of Crete, Greece
fYear
2015
Firstpage
401
Lastpage
410
Abstract
In the Web of data, entities are described by interlinked data rather than documents on the Web. In this work, we focus on entity resolution in the Web of data, i.e., identifying descriptions that refer to the same real-world entity. To reduce the required number of pairwise comparisons, methods for entity resolution perform blocking as a pre-processing step. A blocking technique places similar entity descriptions into blocks and executes comparisons only between descriptions within the same block. We experimentally evaluate blocking techniques proposed for the Web of data and present dataset characteristics that determine the effectiveness and efficiency of such methods. Furthermore, we analyze the characteristics of the missed matching entity descriptions and examine different types of links that blocking techniques can potentially identify.
Keywords
"Erbium","Big data","Semantics","Poles and towers","Context","Clustering algorithms","Conferences"
Publisher
ieee
Conference_Titel
Big Data (Big Data), 2015 IEEE International Conference on
Type
conf
DOI
10.1109/BigData.2015.7363781
Filename
7363781
Link To Document