Identifying Candidate Datasets for Data Interlinking

摘要

One of the design principles that can stimulate the growth and increase the usefulness of the Web of data is URIs linkage. However, the related URIs are typically in different datasets managed by different publishers. Hence, the designer of a new dataset must be aware of the existing datasets and inspect their content to define same As links. This paper proposes a technique based on probabilistic classifiers that, given a datasets S to be published and a set T of known published datasets, ranks each T_i ∈ T according to the probability that links between S and T_i can be found by inspecting the most relevant datasets. Results from our technique show that the search space can be reduced up to 85%, thereby greatly decreasing the computational effort.