- Title
- Analogies between sentences : theoretical aspects - preliminary experiments
- Creator
- Afantenos, Stergos; Kunze, Tarek; Lim, Suryani; Prade, Henri; Richard, Gilles
- Date
- 2021
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/180286
- Identifier
- vital:15718
- Identifier
-
https://doi.org/10.1007/978-3-030-86772-0_1
- Identifier
- ISBN:0302-9743 (ISSN); 9783030867713 (ISBN)
- Abstract
- Analogical proportions hold between 4 items a, b, c, d insofar as we can consider that “a is to b as c is to d”. Such proportions are supposed to obey postulates, from which one can derive Boolean or numerical models that relate vector-based representations of items making a proportion. One basic postulate is the preservation of the proportion by permuting the central elements b and c. However this postulate becomes debatable in many cases when items are words or sentences. This paper proposes a weaker set of postulates based on internal reversal, from which new Boolean and numerical models are derived. The new system of postulates is used to extend a finite set of examples in a machine learning perspective. By embedding a whole sentence into a real-valued vector space, we tested the potential of these weaker postulates for classifying analogical sentences into valid and non-valid proportions. It is advocated that identifying analogical proportions between sentences may be of interest especially for checking discourse coherence, question-answering, argumentation and computational creativity. The proposed theoretical setting backed with promising preliminary experimental results also suggests the possibility of crossing a real-valued embedding with an ontology-based representation of words. This hybrid approach might provide some insights to automatically extract analogical proportions in natural language corpora. © 2021, Springer Nature Switzerland AG.
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Relation
- 16th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2021 Vol. 12897 LNAI, p. 3-18
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright @ Springer Nature Switzerland AG 2021
- Rights
- Open Access
- Full Text
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