Document Type

Conference Proceeding

Source of Publication

Procedia Computer Science

Publication Date

1-1-2016

Abstract

© 2016 The Authors. The value of big data comes from its variety where data is collected from various sources. One of the key big data challenges is identifying which data objects are relevant or refer to the same logical entity across various data sources. This challenge is traditionally known as schema matching. Due to big data velocity traditional approaches to data matching can no longer be used. In this paper we present an approach for inferring data objects correlation. We present our algorithm that relies on the objects meta-data and it consults the Word Net thesaurus.

ISSN

1877-0509

Publisher

Elsevier

Volume

83

First Page

1238

Last Page

1243

Disciplines

Computer Sciences

Keywords

Big data, Schema integration, Semantic Relation ships, Word Net

Scopus ID

84971247430

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Gold: This publication is openly available in an open access journal/series

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