The rapid growth of open and structured RDF data on the Web has promoted the development of dataset search as an important research topic. The core function of existing systems is ad hoc dataset retrieval (AHDR) based on the metadata of datasets, which contains limited information and often suffers from quality issues. To overcome the limitations, in this article, we systematically investigate content-based AHDR to exploit the actual RDF data in datasets. We address three main tasks of content-based AHDR with novel methods for handling the large size and complex structure of RDF data to facilitate dataset retrieval, deduplication, and snippet extraction. These methods are integrated into an online and open-source prototype called Caddie . The effectiveness and practicability of its components are evaluated on a public test collection and by a user study.
Wang et al. (2026) studied this question.