Abstract
Abductive reasoning includes discovering new hypotheses or explanations. This chapter identifies several factors involved in abductive reasoning in an effort to move toward a theory of such reasoning. The chapter has an ultimate focus on the nature and influence of similarity. A major goal of our work is to develop computational tools that provide intelligent abductive suggestions to people engaged in discovering new knowledge. Novel abductive inferences often exhibit interesting similarities to the phenomena under investigation. Such similarities are not strong or direct but rather are often only obvious once the inference has been drawn. Some of our research is directed at discovering indirect similarities from text by using measures that are sensitive to indirect relations between terms in the text. By focusing on terms that are related but do not co-occur, potentially interesting indirect relations can be explored. Our work employs Random Indexing methods and Pathfinder networks to identify and display relations among terms in a text corpus. These displays are provided to individuals to suggest possible abductive inferences. We explore a variety of methods for identifying indirect similarities. The degree to which surprising and interesting inferences are suggested is the primary measure of success. Several examples are presented to illustrate the method: An analysis showing a positive relationship between (a) the strength of indirect similarity in one period of time and (b) the likelihood that the terms involved become directly related in future time This correlation supports the hypothesis that discoveries may be latent in such indirect similarities. Presumably, noticing such similarity brings indirectly related concepts together suggesting a new idea.
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- 1.
The PFNETs presented here were all computed with parameters, r = ∞ and q = n – 1, where n is the number of nodes in the network. The links preserved with these parameters consist of the union of the links in all minimum spanning trees or, in terms of similarities, the union of the links in all maximum spanning trees. The sum of the similarities associated with the links in such trees is the maximum over all possible spanning trees. See “Pathfinder Networks” in Wikipedia for additional information.
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Schvaneveldt, R.W., Cohen, T.A. (2010). Abductive Reasoning and Similarity: Some Computational Tools. In: Ifenthaler, D., Pirnay-Dummer, P., Seel, N. (eds) Computer-Based Diagnostics and Systematic Analysis of Knowledge. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-5662-0_11
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