Abstract
Ad hoc dataset retrieval is a trending topic in IR research. Methods and systems are evolving from metadata-based to content-based ones which exploit the data itself for improving retrieval accuracy but thus far lack a specialized test collection. In this paper, we build and release the first test collection for ad hoc content-based dataset retrieval, where content-oriented dataset queries and content-based relevance judgments are annotated by human experts who are assisted with a dashboard designed specifically for comprehensively and conveniently browsing both the metadata and data of a dataset. We conduct extensive experiments on the test collection to analyze its difficulty and provide insights into the underlying task.
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Lin, T., Chen, Q., Cheng, G., Soylu, A., Ell, B., Zhao, R., … Kharlamov, E. (2022). ACORDAR: A Test Collection for Ad Hoc Content-Based (RDF) Dataset Retrieval. In SIGIR 2022 - Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 2981–2991). Association for Computing Machinery, Inc. https://doi.org/10.1145/3477495.3531729
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