Processing Scientific Networks in Bibliographic Databases

The paper presents a knowledge-based model for processing network-like relationships between scientists in bibliographic databases. The need to reason about scientific structures has turned out to be a remaining problem in the field of person-related Information Retrieval (IR) considering research contexts. The method, which is introduced here, determines science-structural relationships between all scientists in sample domains of a database including their semantic proximity. As an expressive description of the “world” studied at an instantaneous point of time, such networks of personal relations can be used to draw inferences concerning the importance of scientists for a certain topic in regard to their structural position within a complete “research landscape”.