Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Literature Mining: Towards Better Understanding of Autism
AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
Literature mining method RaJoLink for uncovering relations between biomedical concepts
Journal of Biomedical Informatics
Performance Analysis of Class Noise Detection Algorithms
Proceedings of the 2010 conference on STAIRS 2010: Proceedings of the Fifth Starting AI Researchers' Symposium
Outlier Detection in Cross-Context Link Discovery for Creative Literature Mining
The Computer Journal
Exploring the power of outliers for cross-domain literature mining
Bisociative Knowledge Discovery
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In literature-based creative knowledge discovery the goal is to identify interesting terms or concepts which relate different domains. We propose to support this cross-context link discovery process by inspecting outlier documents which are not in the mainstream domain literature. We have explored the utility of outlier documents, discovered by combining three classification-based outlier detection methods, in terms of their potential for bridging concept discovery in the migraine-magnesium cross-domain discovery problem and in the autism-calcineurin domain pair. Experimental results prove that outlier documents present a small fraction of a domain pair dataset that is rich on concept bridging terms. Therefore, by exploring only a small subset of documents, where a great majority of bridging terms are present and more frequent, the effort needed for finding cross-domain links can be substantially reduced.