Best Practices

This work has been created in the PROMISE network of excellence (contract n. 258191) as a part of the 7th Framework Program of the European commission (FP7/2007-2013).

Martin Braschler, Stefan Rietberger, Melanie Imhof, Zurich University of Applied Sciences
Anni Järvelin, Preben Hansen, Swedish Institude of Compute Science / University of Gothenburg
Mihai Lupu, Vienna University of Technology
Maria Gäde, Humboldt University
Richard Berendsen, University of Amsterdam
Alba Garcia Seco de Herrera, University of Applied Sciences and Arts Western Switzerland

Abstract

This report presents best practice recommendations for information retrieval (IR) system developers, IR application implementers and IR application maintainers. It covers the main aspects of IR systems and applications, as well as recommendations for the user interface and evaluation. The best practices presented are the result of a distillation of academic IR output, taken mainly from experiments conducted within the confines of the CLEF evaluation campaigns, but also from additional sources. Elaboration was carried out both as a manual, intellectual effort, but also using semi-automatic, statistical methods that provided additional evidence for validation. Information retrieval technology is today used for very diverse purposes, supporting a range from "classical" search engines to applications such as topic detection or recommender systems. It is thus important to provide context to the individual recommendations. The report proposes a structure for the different best practice recommendations that states limitations and qualifications for different use case domains, and is prepared to include direct links to experiments and tested configurations in the future.

Resources

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