SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Toward principles for the design of ontologies used for knowledge sharing
International Journal of Human-Computer Studies - Special issue: the role of formal ontology in the information technology
Journal of the American Society for Information Science
Semantic Road Maps for Literature Searchers
Journal of the ACM (JACM)
Concept decompositions for large sparse text data using clustering
Machine Learning
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Self-Organizing Maps
IV '00 Proceedings of the International Conference on Information Visualisation
TopCat: Data Mining for Topic Identification in a Text Corpus
IEEE Transactions on Knowledge and Data Engineering
Text mining techniques for patent analysis
Information Processing and Management: an International Journal
Text document clustering based on frequent word meaning sequences
Data & Knowledge Engineering
Structuring technological information for technology roadmapping: data mining approach
AIKED'08 Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases
A global map of science based on the ISI subject categories
Journal of the American Society for Information Science and Technology
@Note: A workbench for Biomedical Text Mining
Journal of Biomedical Informatics
Using text mining and sentiment analysis for online forums hotspot detection and forecast
Decision Support Systems
Text classification using graph mining-based feature extraction
Knowledge-Based Systems
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With the growing recognition of the importance of knowledge creation, knowledge maps are being regarded as a critical tool for successful knowledge management. However, the various methods of developing knowledge maps mostly depend on unsystematic processes and the judgment of domain experts with a wide range of untapped information. Thus, this research aims to propose a new approach to generate knowledge maps by mining document databases that have hardly been examined, thereby enabling an automatic development process and the extraction of significant implications from the maps. To this end, the accepted research proposal database of the Korea Research Foundation (KRF), which includes a huge knowledge repository of research, is investigated for inducing a keyword-based knowledge map. During the developmental process, text mining plays an important role in extracting meaningful information from documents, and network analysis is applied to visualize the relations between research categories and measure the value of network indices. Five types of knowledge maps (core R&D map, R&D trend map, R&D concentration map, R&D relation map, and R&D cluster map) are developed to explore the main research themes, monitor research trends, discover relations between R&D areas, regions, and universities, and derive clusters of research categories. The results can be used to establish a policy to support promising R&D areas and devise a long-term research plan.