Information for "SLINT: A Schema-Independent Linked Data Interlinking System"

Linked data interlinking is the discovery of all instances that represent the same real-world object and locate in different data sources. Since different data publishers frequently use different schemas for storing resources, we aim at developing a schema-independent interlinking system. Our system automatically selects important predicates and useful predicate alignments, which are used as the key for blocking and instance matching. The key distinction of our system is the use of weighted co-occurrence and adaptive filtering in blocking and instance matching. Experimental results show that the system highly improves the precision and recall over some recent ones. The performance of the system and the efficiency of main steps are also discussed.

Although SLINT has good result on tested datasets, it is not sufficient to evaluate the scalability of our system, which we consider as the current limiting point because of the used of weighted co-occurrence matrix. We will investigate about a solution for this issue in our next work. Besides, we also interested in automatic configuration for every threshold used in SLINT and improving SLINT into a novel cross-domain interlinking system.