Abstract
The central idea behind Case-Based Reasoning has always been the notion that reasoning can be supported using memories of past problem solving. One bottleneck in this work has often been the development of case libraries needed to support this reasoning rather than the transformation of the cases themselves. In much of our work, we have taken an approach in which we treat web-recourses as the distributed knowledge engineering that can be integrated into memory- or case-based reasoning systems. We have been working on how we can take the core view of “Reasoning as Remembering” and transform it into “Reasoning as Search”. The primary issues in this work are how to map problem-solving or task needs onto the queries required to find initial candidates, filter those candidates for relevance and then manage the exploitation of the results. I will outline how we have done this in two systems we have built recently, News at Seven and Baleen, systems that track the world of social media, news and the Web to support narrative generation.
Some of this material is based upon work supported by the National Science Foundation under Grants No. III-0917261 and 0535231. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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© 2011 Springer-Verlag Berlin Heidelberg
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Hammond, K.J. (2011). Reasoning as Search: Supporting Reasoning with Distributed Memory. In: Ram, A., Wiratunga, N. (eds) Case-Based Reasoning Research and Development. ICCBR 2011. Lecture Notes in Computer Science(), vol 6880. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23291-6_1
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DOI: https://doi.org/10.1007/978-3-642-23291-6_1
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