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Mutschke, P.; Mayr, P.: Science models for search : a study on combining scholarly information retrieval and scientometrics (2015)
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Mayr, P.; Mutschke, P.; Petras, V.; Schaer, P.; Sure, Y.: Applying science models for search (2010)
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- Abstract
- The paper proposes three different kinds of science models as value-added services that are integrated in the retrieval process to enhance retrieval quailty. The paper discusses the approaches Search Term Recommendation, Bradfordizing and Author Centrality on a general level and addresses implementation issues of the models within a real-life retrieval environment.
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Mayr, P.; Schaer, P.; Mutschke, P.: ¬A science model driven retrieval prototype (2011)
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- Abstract
- This paper is about a better understanding of the structure and dynamics of science and the usage of these insights for compensating the typical problems that arises in metadata-driven Digital Libraries. Three science model driven retrieval services are presented: co-word analysis based query expansion, re-ranking via Bradfordizing and author centrality. The services are evaluated with relevance assessments from which two important implications emerge: (1) precision values of the retrieval services are the same or better than the tf-idf retrieval baseline and (2) each service retrieved a disjoint set of documents. The different services each favor quite other - but still relevant - documents than pure term-frequency based rankings. The proposed models and derived retrieval services therefore open up new viewpoints on the scientific knowledge space and provide an alternative framework to structure scholarly information systems.
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