Research project: Automatic translation system by particle
swarm optimization
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<< TO BE UPDATED, PLEASE
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The present project proposes a new
approach to measuring efficiency of
Natural Language-based
Machine Translation. We implement some attributes of
evolutionary algorithms
performing cosine similarity objective function of a
Particle Swarm Optimization
(PSO) algorithm then, we evaluate an English text set for
translation precision into the Spanish text as a simulated
benchmark, and explore the backward process. Our results
show that PSO algorithm can be used for
translation of multiple language
sentences with one identifier only, in other words the
technology presented is language-pair independent.
Specifically, we indicate that our
cosine similarity
objective function improves the velocity attribute of the
PSO algorithm, making the complex cost functions unnecessary
[1]. |
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Publications: |
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Research papers: |
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[1] Montes Olguín J.A.,
Mizera-Pietraszko J., Rodriguez Jorge R.,
Martínez García E.A. (2018)
Particle Swarm Optimization as a
New Measure of Machine Translation Efficiency. In: Abraham
A., Haqiq A., Muda A., Gandhi N. (eds) Proceedings of the
Ninth International Conference on Soft Computing and Pattern
Recognition (SoCPaR 2017). SoCPaR 2017. Advances in
Intelligent Systems and Computing, vol 737. Springer, Cham.(Web
of Science, Procceddings Citation Index). |
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[2] Jolanta
MIZERA-PIETRASZKO, Ricardo RODRIGUEZ JORGE,
Grzegorz KOŁACZEK, Edgar Alonso MARTINEZ GARCIA,
"Information Streaming Systems: A Review", Intelligent
Systems and Applications (INISTA) 2018 Innovations in,
pp. 1-9, 2018.(Web
of Science, Procceddings Citation Index). |
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[3]Mizera-Pietraszko, Jolanta; Kolaczek, Grzegorz; Rodriguez
Jorge, Ricardo;
Martínez García, Edgar Alonso, Information
Streaming Systems: A Review, The 2018 IEEE International
Conference on INnovations in Intelligent SysTems and
Applications (INISTA 2018), July 3-5, 2018, Thessaloniki,
Greece.(Web
of Science, Procceddings Citation Index). |
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