Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
Journal of Computational and Applied Mathematics
Journal of the American Society for Information Science and Technology
Detecting research topics via the correlation between graphs and texts
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Combining full text and bibliometric information in mapping scientific disciplines
Information Processing and Management: an International Journal - Special issue: Infometrics
Novel labeling strategies for hierarchical representation of multidimensional data analysis results
AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Mining Research Topics Evolving Over Time Using a Diachronic Multi-source Approach
ICDMW '10 Proceedings of the 2010 IEEE International Conference on Data Mining Workshops
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The notion of `core documents', first introduced in the context of co-citation analysis and later re-introduced for bibliographic coupling and extended to hybrid approaches, refers to the representation of the core of a document set according to given criteria. In the present study, core documents are used for the identification of new emerging topics. The proposed method proceeds from independent clustering of disciplines in different time windows. Cross-citations between core documents and clusters in different periods are used to detect new, exceptionally growing clusters or clusters with changing topics. Three paradigmatic types of new, emerging topics are distinguished. Methodology is illustrated using the example of four ISI subject categories selected from the life sciences, applied sciences and the social sciences.