Grün, S.; Poley, C: Statistische Analysen von Semantic Entities aus Metadaten- und Volltextbeständen von German Medical Science (2017)
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- Abstract
- This paper analyzes the information content of metadata and full texts in German Medical Science (GMS) articles in English language. The object of the study is to compare semantic entities that are used to enrich GMS metadata (titles and abstracts) and GMS full texts. The aim of the study is to test whether using full texts increases the value added information. The comparison and evaluation of semantic entities was done statistically. Measures of descriptive statistics were gathered for this purpose. In addition to the ratio of central tendencies and scatterings, we computed the overlaps and complements of the values. The results show a distinct increase of information when full texts are added. On average, metadata contain 25 different entities and full texts 215. 89% of the concepts in the metadata are also represented in the full texts. Hence, 11% of the metadata concepts are found in the metadata only. In summary, the results show that the addition of full texts increases the informational value, e.g. for information retrieval processes.
- Source
- GMS Medizin-Bibliothek-Information. 17(2017) no.3, S.1-5
