CiteSpace II: visualization and knowledge discovery in bibliographic databases.

Abstract

This article presents a description and case study of CiteSpace II, a Java application which supports visual exploration with knowledge discovery in bibliographic databases. Highly cited and pivotal documents, areas of specialization within a knowledge domain, and emergence of research topics are visually mapped through a progressive knowledge domain visualization approach to detecting and visualizing trends and patterns in scientific literature. The test case in this study is progressive knowledge domain visualization of the field of medical informatics. Datasets based on publications from twelve journals in the medical informatics field covering the time period from 1964-2004 were extracted from PubMed and Web of Science (WOS) and developed as testbeds for evaluation of the CiteSpace system. Two resulting document-term co-citation and MeSH term co-occurrence visualizations are qualitatively evaluated for identification of pivotal documents, areas of specialization, and research trends. Practical applications in bio-medical research settings are discussed.

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No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 884 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.