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RSS FeedsAlgorithms, Vol. 12, Pages 26: Ensemble and Deep Learning for Language-Independent Automatic Selection of Parallel Data (Algorithms)

 
 

19 january 2019 23:01:36

 
Algorithms, Vol. 12, Pages 26: Ensemble and Deep Learning for Language-Independent Automatic Selection of Parallel Data (Algorithms)
 




Machine translation is used in many applications in everyday life. Due to the increase of translated documents that need to be organized as useful or not (for building a translation model), the automated categorization of texts (classification), is a popular research field of machine learning. This kind of information can be quite helpful for machine translation. Our parallel corpora (English-Greek and English-Italian) are based on educational data, which are quite difficult to translate. We apply two state of the art architectures, Random Forest (RF) and Deeplearnig4j (DL4J), to our data (which constitute three translation outputs). To our knowledge, this is the first time that deep learning architectures are applied to the automatic selection of parallel data. We also propose new string-based features that seem to be effective for the classifier, and we investigate whether an attribute selection method could be used for better classification accuracy. Experimental results indicate an increase of up to 4% (compared to our previous work) using RF and rather satisfactory results using DL4J.


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177 viewsCategory: Informatics
 
Algorithms, Vol. 12, Pages 18: A Novel Hybrid Ant Colony Optimization for a Multicast Routing Problem (Algorithms)
Algorithms, Vol. 12, Pages 25: Power Allocation Algorithm for an Energy-Harvesting Wireless Transmission System Considering Energy Losses (Algorithms)
 
 
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