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Inducing semantic relations from conceptual spaces: A data-driven approach to plausible reasoning
2015
Artificial Intelligence
Commonsense reasoning patterns such as interpolation and a fortiori inference have proven useful for dealing with gaps in structured knowledge bases. An important di culty in applying these reasoning patterns in practice is that they rely on fine-grained knowledge of how di↵erent concepts and entities are semantically related. In this paper, we show how the required semantic relations can be learned from a large collection of text documents. To this end, we first induce a conceptual space from
doi:10.1016/j.artint.2015.07.002
fatcat:3m6qpscx3rforjr23ltil2wl4i