With GESIS Search, researchers can find social science research datasets, variables from questionnaires, measurement instruments & tools, publications, and documents from the GESIS Library and the GESIS web in one integrated system.
We have newly integrated a module that shows recommendations for similar documents. For example, similar research data sets are presented for the Generation Z dataset or similar publications for a publication on migration. The integration and evaluation of recommendations are based on the STELLA evaluation framework. It allows for testing different recommender algorithms in real user environments. In GESIS Search, various recommender variants are integrated and evaluated against one another. We provide recommendations based on the similarity between documents, for example, the syntactic similarity between documents, such as titles and abstracts, or the semantic similarity when documents describe very similar content. In our evaluation scenario, the user decides on the best-performing recommender based on their click behavior. The more clicks a certain recommender achieves, the better it is evaluated.
Recommendations for the Generation Z dataset.
Recommendations for a publication on the topic of migration.