TY  - JOUR
AU  - B. Gautam
AU  - Oriol Ramos Terrades
AU  - Joana Maria Pujadas-Mora
AU  - Miquel Valls-Figols
PY  - 2020//
TI  - Knowledge graph based methods for record linkage
T2  - PRL
JO  - Pattern Recognition Letters
SP  - 127
EP  - 133
VL  - 136
N2  - Nowadays, it is common in Historical Demography the use of individual-level data as a consequence of a predominant life-course approach for the understanding of the demographic behaviour, family transition, mobility, etc. Advanced record linkage is key since it allows increasing the data complexity and its volume to be analyzed. However, current methods are constrained to link data from the same kind of sources. Knowledge graph are flexible semantic representations, which allow to encode data variability and semantic relations in a structured manner.In this paper we propose the use of knowledge graph methods to tackle record linkage tasks. The proposed method, named WERL, takes advantage of the main knowledge graph properties and learns embedding vectors to encode census information. These embeddings are properly weighted to maximize the record linkage performance. We have evaluated this method on benchmark data sets and we have compared it to related methods with stimulating and satisfactory results.
UR  - https://www.sciencedirect.com/science/article/pii/S0167865520301823
L1  - http://refbase.cvc.uab.es/files/GRP2020.pdf
N1  - DAG; 600.140; 600.121
ID  - B. Gautam2020
ER  -