Reducing the Search Space in Literature-Based Discovery by Exploring Outlier Documents: a Case Study in Finding Links Between Gut Microbiome and Alzheimer’s Disease

Bojan Cestnik, Elsa Fabbretti, Donatella Gubiani, Tanja Urbančič, Nada Lavrač

GCB, Vol. 3, No. 3 (2017): e58


Literature-based discovery tools have been often used to overcome the problem of fragmentation of science and to assist researchers in their process of cross-domain knowledge discovery. In this paper we propose a methodology for cross-domain literature-based discovery that focuses on outlier documents to reduce the search space of potential cross-domain links and to improve search efficiency. In a previous study, literature mining tools OntoGen for document clustering and CrossBee for cross-domain bridging term exploration were combined to search for hidden relations in scientific papers from two different domains of interest, where the utility of the approach was demonstrated in a study involving PubMed papers about Alzheimer’s disease and gut microbiome. This paper extends the approach by proposing a methodology, implemented as a repeatable workflow in a web-based text mining platform TextFlows, which enables easy access and execution of the methodology for the interested researcher.


Literature-based discovery, cross-domain discovery, outliers, workflows, gut microbiome, Alzheimer Disease

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Copyright (c) 2017 Bojan Cestnik, Elsa Fabbretti, Donatella Gubiani, Tanja Urbančič, Nada Lavrač

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