An interactive system for finding complementary literatures: a stimulus to scientific discovery
Artificial Intelligence - Special issue on scientific discovery
Using latent semantic indexing for literature based discovery
Journal of the American Society for Information Science
Literature-based discovery by lexical statistics
Journal of the American Society for Information Science
Journal of the American Society for Information Science and Technology
Literature-based discovery on the World Wide Web
ACM Transactions on Internet Technology (TOIT)
LitLinker: capturing connections across the biomedical literature
Proceedings of the 2nd international conference on Knowledge capture
Text mining: generating hypotheses from MEDLINE
Journal of the American Society for Information Science and Technology
Interaction design for literature-based discovery
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Letter to the Editor: Validating discovery in literature-based discovery
Journal of Biomedical Informatics
Reply: Response to ''Validating discovery in literature-based discovery"
Journal of Biomedical Informatics
Evaluating organization external knowledge acquisition
Proceedings of the 1st international conference on Forensic applications and techniques in telecommunications, information, and multimedia and workshop
Literature mining method RaJoLink for uncovering relations between biomedical concepts
Journal of Biomedical Informatics
A new evaluation methodology for literature-based discovery systems
Journal of Biomedical Informatics
RaJoLink: A Method for Finding Seeds of Future Discoveries in Nowadays Literature
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Journal of Biomedical Informatics
Mining connections between chemicals, proteins, and diseases extracted from Medline annotations
Journal of Biomedical Informatics
Methodological Review: Text mining for traditional Chinese medical knowledge discovery: A survey
Journal of Biomedical Informatics
Passage retrieval based hidden knowledge discovery from biomedical literature
Expert Systems with Applications: An International Journal
Bisociative knowledge discovery by literature outlier detection
Bisociative Knowledge Discovery
Journal of Information Science
A graph-based recovery and decomposition of Swanson's hypothesis using semantic predications
Journal of Biomedical Informatics
Results on mining NHANES data: A case study in evidence-based medicine
Computers in Biology and Medicine
MedRank: discovering influential medical treatments from literature by information network analysis
ADC '13 Proceedings of the Twenty-Fourth Australasian Database Conference - Volume 137
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The explosive growth in biomedical literature has made it difficult for researchers to keep up with advancements, even in their own narrow specializations. While researchers formulate new hypotheses to test, it is very important for them to identify connections to their work from other parts of the literature. However, the current volume of information has become a great barrier for this task and new automated tools are needed to help researchers identify new knowledge that bridges gaps across distinct sections of the literature. In this paper, we present a literature-based discovery system called LitLinker that incorporates knowledge-based methodologies with a statistical method to mine the biomedical literature for new, potentially causal connections between biomedical terms. We demonstrate LitLinker's ability to capture novel and interesting connections between diseases and chemicals, drugs, genes, or molecular sequences from the published biomedical literature. We also evaluate LitLinker's performance by using the information retrieval metrics of precision and recall.