ACORDAR: A Test Collection for Ad Hoc Content-Based (RDF) Dataset Retrieval
Lin, Tengteng; Chen, Qiaosheng; Cheng, Gong; Soylu, Ahmet; Ell, Basil; Zhao, Ruoqi; Shi, Qing; Wang, Xiaxia; Gu, Yu; Kharlamov, Evgeny
Conference object
Accepted version
Permanent lenke
https://hdl.handle.net/11250/3064165Utgivelsesdato
2022Metadata
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Originalversjon
http://dx.doi.org/10.1145/3477495.3531729Sammendrag
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.