1. Outlier Detection in Cross-Context Link Discovery for Creative Literature Mining.
- Author
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Petrič, Ingrid, Cestnik, Bojan, Lavrač, Nada, and Urbančič, Tanja
- Subjects
INTRUSION detection systems (Computer security) ,TEXT mining ,SOCIOECONOMIC factors ,INFORMATION & communication technologies ,DATA mining ,COMPUTER network resources - Abstract
This paper investigates the role of outliers in literature-based knowledge discovery. It shows that detecting interesting outliers which appear in the literature on a given phenomenon can help the expert to find implicit relationships among concepts of different domains. The underlying assumption is that while the majority of articles in the given scientific domain describe matters related to a common understanding of the domain, the exploration of outliers may lead to the detection of scientifically interesting bridging concepts among disjoint sets of scientific articles. The proposed approach contributes to cross-context link discovery by proving the utility of outlier detection for finding bisociative links in the process of autism literature exploration, as well as by uncovering implicit relationships in the articles from the migraine domain. [ABSTRACT FROM AUTHOR]
- Published
- 2012
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