Geodesic
Conflict Resolution Using Relation Classification: High-Level Data Fusion in Data Integration
Computer Science and Information Systems, Tome 18 (2021) no. 3.

Voir la notice de l'article provenant de la source Computer Science and Information Systems website

The aim of conflict resolution in data integration systems is to identify the true values from among different and conflicting claims about a single entity provided by different data sources. Most data fusion methods for resolving conflicts between entities are based on two estimated parameters: the truthfulness of data and the trustworthiness of sources. The relations between entities are however an additional source of information that can be used in conflict resolution. In this article, we seek to bridge the gap between two important broad areas, relation estimation and truth discovery, and to demonstrate that there is a natural synergistic relationship between machine learning and data fusion. Specifically, we use relational machine learning methods to estimate the relations between entities, and then use these relations to estimate the true value using some fusion functions. An evaluation of the results shows that our proposed approach outperforms existing conflict resolution techniques, especially where there are few reliable sources.
Keywords: conflict resolution, data fusion, relational machine learning, relation estimation, relation classification 
@article{CSIS_2021_18_3_a22,
     author = {Zeinab Nakhaei and Ali Ahmadi and Arash Sharifi and Kambiz Badie},
     title = {Conflict {Resolution} {Using} {Relation} {Classification:} {High-Level} {Data} {Fusion} in {Data} {Integration}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {18},
     number = {3},
     year = {2021},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2021_18_3_a22/}
}
TY  - JOUR
AU  - Zeinab Nakhaei
AU  - Ali Ahmadi
AU  - Arash Sharifi
AU  - Kambiz Badie
TI  - Conflict Resolution Using Relation Classification: High-Level Data Fusion in Data Integration
JO  - Computer Science and Information Systems
PY  - 2021
VL  - 18
IS  - 3
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/CSIS_2021_18_3_a22/
ID  - CSIS_2021_18_3_a22
ER  - 
%0 Journal Article
%A Zeinab Nakhaei
%A Ali Ahmadi
%A Arash Sharifi
%A Kambiz Badie
%T Conflict Resolution Using Relation Classification: High-Level Data Fusion in Data Integration
%J Computer Science and Information Systems
%D 2021
%V 18
%N 3
%I mathdoc
%U http://geodesic.mathdoc.fr/item/CSIS_2021_18_3_a22/
%F CSIS_2021_18_3_a22
Zeinab Nakhaei; Ali Ahmadi; Arash Sharifi; Kambiz Badie. Conflict Resolution Using Relation Classification: High-Level Data Fusion in Data Integration. Computer Science and Information Systems, Tome 18 (2021) no. 3. http://geodesic.mathdoc.fr/item/CSIS_2021_18_3_a22/