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Abstract
Background:
Systematic literature searches (SLS) are a core element of systematic reviews (SR) in evidence-based medicine. Ideally, for reasons of quality assurance, they follow a strictmethodology:
they have not only to be comprehensive, exhaustive and error-robust, but also documented by a protocol. Main sources for systematic reviews are original works, usually published in journals and referenced in bibliographic databases. Due to systematic distortions of the literary landscape (1), clinical trial registries and grey literature as sources of information are becoming increasingly relevant in recent years. This makes searching a resource-consuming process in which the development of optimal and reproduceable search strategies with a focus on optimizing recall and precision is a crucial task (2).Successful efforts were made to support individual steps of the LSP through text mining applications (3–7), but a systematic classification of those methods and tools in the context of search and retrieval processes is still missing (4, 5), as well as a complete framework of effective strategies in SLS (8).