Abstract
Explanatory analogies make learning complex concepts easier by elaborately mapping a target concept onto a more familiar source concept. Solutions exist for automatically retrieving shorter metaphors from natural language text, but not for explanatory analogies. In this paper, we propose an approach to find webpages containing explanatory analogies for a given target concept. For this, we propose the use of a ‘region of interest’ (ROI) based on the observation that linguistic markers and source concept often co-occur with various forms of the word ‘analogy’. We also suggest an approach to identify the source concept(s) contained in a retrieved analogy webpage. We demonstrate these approaches on a dataset created using Google custom search to find candidate web pages that may contain analogies.
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Kumar, V., Bhat, S., Pedanekar, N. (2014). Automatically Retrieving Explanatory Analogies from Webpages. In: de Rijke, M., et al. Advances in Information Retrieval. ECIR 2014. Lecture Notes in Computer Science, vol 8416. Springer, Cham. https://doi.org/10.1007/978-3-319-06028-6_45
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DOI: https://doi.org/10.1007/978-3-319-06028-6_45
Publisher Name: Springer, Cham
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