Evaluation Infrastructures for Academic Shared Tasks Requirements and Concept Design for Search and Recommendation Scenarios

• Published in: Datenbank-Spektrum : Zeitschrift für Datenbanktechnologie : Organ der Fachgruppe Datenbanken der Gesellschaft für Informatik e.V Vol. 20; no. 1; pp. 29 - 36
• Main Authors: Schaible, Johann, Breuer, Timo, Tavakolpoursaleh, Narges, Müller, Bernd, Wolff, Benjamin, Schaer, Philipp
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-03-2020
• Subjects: Computer Science; Computer Systems Organization and Communication Networks; Data Mining and Knowledge Discovery; Data Structures and Information Theory; Database Management; Information Storage and Retrieval; IT in Business; Schwerpunktbeitrag; Online/Offline Evaluation; Evaluation Infrastructures; Domain-Specific Academic Search; Reproducibility
• ISSN: 1618-2162; 1610-1995
• DOI: 10.1007/s13222-020-00335-x

Academic search systems aid users in finding information covering specific topics of scientific interest and have evolved from early catalog-based library systems to modern web-scale systems. However, evaluating the performance of the underlying retrieval approaches remains a challenge. An increasing amount of requirements for producing accurate retrieval results have to be considered, e.g., close integration of the system’s users. Due to these requirements, small to mid-size academic search systems cannot evaluate their retrieval system in-house. Evaluation infrastructures for shared tasks alleviate this situation. They allow researchers to experiment with retrieval approaches in specific search and recommendation scenarios without building their own infrastructure. In this paper, we elaborate on the benefits and shortcomings of four state-of-the-art evaluation infrastructures on search and recommendation tasks concerning the following requirements: support for online and offline evaluations, domain specificity of shared tasks, and reproducibility of experiments and results. In addition, we introduce an evaluation infrastructure concept design aiming at reducing the shortcomings in shared tasks for search and recommender systems.