Selecting the Links in BisoNets Generated from Document Collections

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Selecting the Links in BisoNets Generated from Document Collections
According to Koestler, the notion of a bisociation denotes a connection between pieces of information from habitually separated domains or categories. In this paper, we consider a methodology to find such bisociations using a network representation of knowledge, which is called a BisoNet, because it promises to contain bisociations. In a first step, we consider how to create BisoNets from several textual databases taken from different domains using simple text-mining techniques. To achieve this, we introduce a procedure to link nodes of a BisoNet and to endow such links with weights, which is based on a new measure for comparing text frequency vectors. In a second step, we try to rediscover known bisociations, which were originally found by a human domain expert, namely indirect relations between migraine and magnesium as they are hidden in medical research articles published before 1987. We observe that these bisociations are easily rediscovered by simply following the strongest li...
Marc Segond, Christian Borgelt
Added 26 Jan 2011
Updated 26 Jan 2011
Type Journal
Year 2010
Where IDA
Authors Marc Segond, Christian Borgelt
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