TY - JOUR

T1 - Solving analogical equations between strings of symbols using neural networks

AU - Kaveeta, Vivatchai

AU - Lepage, Yves

N1 - Funding Information:
This work was supported by a JSPS Grant, Number 15K00317 (Kakenhi C), entitled Language productivity: efficient extraction of productive analogical clusters and their evaluation using statistical machine translation.
Publisher Copyright:
Copyright © 2016 for this paper by its authors.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

PY - 2016

Y1 - 2016

N2 - A neural network model to solve analogical equations between strings of symbols is proposed. The method transforms the input strings into two fixed size alignment matrices. The matrices act as the input of the neural network which predicts two output matrices. Finally, a string decoder transforms the predicted matrices into the final string output. By design, the neural network is constrained by several properties of analogy. The experimental results show a fast learning rate with a high prediction accuracy that can beat a baseline algorithm.

AB - A neural network model to solve analogical equations between strings of symbols is proposed. The method transforms the input strings into two fixed size alignment matrices. The matrices act as the input of the neural network which predicts two output matrices. Finally, a string decoder transforms the predicted matrices into the final string output. By design, the neural network is constrained by several properties of analogy. The experimental results show a fast learning rate with a high prediction accuracy that can beat a baseline algorithm.

KW - Neural networks

KW - Proportional analogy

UR - http://www.scopus.com/inward/record.url?scp=85017362541&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85017362541&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85017362541

VL - 1815

SP - 67

EP - 76

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

T2 - 24th International Conference on Case-Based Reasoning Workshops, ICCBR-WS 2016

Y2 - 31 October 2016 through 2 November 2016

ER -