PHOAKS: a system for sharing recommendations
Communications of the ACM
Data mining methods for knowledge discovery
Data mining methods for knowledge discovery
Expertise recommender: a flexible recommendation system and architecture
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Information Retrieval
Machine Learning
Mining a web citation database for author co-citation analysis
Information Processing and Management: an International Journal
Discovering Relevant Scientific Literature on the Web
IEEE Intelligent Systems
An Agent Based Approach to Finding Expertise
PAKM '02 Proceedings of the 4th International Conference on Practical Aspects of Knowledge Management
An Expertise Recommender Using Web Mining
Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference
Research intelligence involving information retrieval - An example of conferences and journals
Expert Systems with Applications: An International Journal
Information Processing and Management: an International Journal
Topological space for attributes set of a formal context
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Discovery and visualization of expertise in a scientific community
Proceedings of the 7th International Conference on Frontiers of Information Technology
Using formal concept analysis to leverage ontology-based Yoga knowledge system
WSEAS Transactions on Information Science and Applications
Conceptual-driven classification for coding advise in health insurance reimbursement
Artificial Intelligence in Medicine
Expert Systems with Applications: An International Journal
A lattice-based approach for mathematical search using Formal Concept Analysis
Expert Systems with Applications: An International Journal
Information Processing and Management: an International Journal
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Current citation-based document retrieval systems generally offer only limited search facilities, such as author search. In order to facilitate more advanced search functions, we have developed a significantly improved system that employs two novel techniques: Context-based Cluster Analysis (CCA) and Context-based Ontology Generation frAmework (COGA) CCA aims to extract relevant information from clusters originally obtained from disparate clustering methods by building relationships between them. The built relationships are then represented as formal context using the Formal Concept Analysis (FCA) technique. COGA aims to generate ontology from clusters relationship built by CCA. By combining these two techniques, we are able to perform ontology learning from a citation database using clustering results. We have implemented the improved system and have demonstrated its use for finding research domain expertise. We have also conducted performance evaluation on the system and the results are encouraging.