Résumé
DLinker is a system for matching instances of two RDF data sources. Its performance is mainly based on the deep comparison of literals. The main comparison algorithm is based on the search for the longest common subsequence (LCS) present in the literals. The validation of the similarity between two literals is performed by a mathematical formula. This formula computes the confidence percentage of the similarity between the literals and compares it with a threshold provided as input among the expected hyperparameters. To validate the similar instances, our system validates only the instances that have reached the value of the acceptation threshold provided in the list of required hyperparameters. The current version focuses on the processing of strings on the spot without taking into account synonyms to make its decisions. This is DLinker's first participation in the OAEI campaign on two principal tracks (SPIMBENCH and SPATIAL) with 9 challenges. DLinker demonstrated its ability to process different data with good accuracy and in a very short time. Additionally, in the context of the SPATIAL challenge DLinker has outperformed the state of the art finishing first with the shortest time. Overall, DLinker exposes different strengths and weaknesses that are discussed in this work.