Algorithms for clustering data
Algorithms for clustering data
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Meta-clustering of gene expression data and literature-based information
ACM SIGKDD Explorations Newsletter
Document Clustering Description Extraction and Its Application
ICCPOL '09 Proceedings of the 22nd International Conference on Computer Processing of Oriental Languages. Language Technology for the Knowledge-based Economy
Topic-driven multi-type citation network analysis
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
Toward generic title generation for clustered documents
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
Hi-index | 0.00 |
In the present study results of an earlier pilot study by Glenisson, Glanzel and Persson are extended on the basis of larger sets of papers. Full text analysis and traditional bibliometric methods are serially combined to improve the efficiency of the two individual methods. The text mining methodology already introduced in the pilot study is applied to the complete publication year 2003 of the journal Scientometrics. Altogether 85 documents that can be considered research articles or notes have been selected for this exercise. The outcomes confirm the main results of the pilot study, namely, that such hybrid methodology can be applied to both research evaluation and information retrieval. Nevertheless, Scientometrics documents published in 2003 cover a much broader and more heterogeneous spectrum of bibliometrics and related research than those analysed in the pilot study. A modified subject classification based on the scheme used in an earlier study by Schoepflin and Glanzel has been applied for validation purposes.