The thematic and citation structures of Data and Knowledge Engineering (DKE) (1985-2007) are identified based on text analysis and citation analysis of the bibliographic records of full papers published in the journal. Temporal patterns are identified by detecting abrupt increases of frequencies of noun phrases extracted from titles and abstracts of DKE papers over time. Conceptual structures of the subject domain are identified by clustering analysis. Concept maps and network visualizations are presented to illustrate salient patterns and emerging thematic trends. A variety of statistics are reported to highlight key contributors and DKE papers that have made profound impacts.
Bibliographical noteFunding Information:
This work is in part supported by the National Science Foundation under Grant No. 0612129. The authors would like to thank for Elsevier and in particular Patrick Gibbons for arranging the access to Scopus and ScienceDirect.
All Science Journal Classification (ASJC) codes
- Information Systems and Management