Intelligent system for English translation using automated knowledge base

2020 ◽  
Vol 39 (4) ◽  
pp. 5057-5066
Author(s):  
Shengqin Bi
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Base ◽  
Machine Translation ◽  
English Translation ◽  
Experimental Simulation ◽  
K Value ◽  
Artificial Intelligence Technology ◽  
Hybrid Recommendation ◽  
Very High

In the process of globalization, machine translation has undergone a long period of evolution and development. Although the development level of machine translation has been greatly improved, the quality of machine translation is still not very high, and it is difficult to meet the needs of users. Artificial intelligence is the science that studies the laws of human intelligent activity. The application of artificial intelligence technology in the English depression and depression, combined with the Internet and intelligent knowledge base, can develop English translation systems to solve the problem of English translation to a certain extent. Based on the above background, the research content of this article is a neural network-based artificial intelligence technology English translation system based on the intelligent knowledge base. This article is mainly based on the existing English-Chinese machine translation to find a more favorable method for English long sentence translation. By improving part-of-speech tagging and rules, the rules can match more sentence patterns to improve the quality of existing machine translations. This paper proposes an improved hybrid recommendation algorithm, and through experimental simulation, the results show that the accuracy of the algorithm is not very high. The highest is 35.64%. The possible reason may be that the k value is selected during k-means text clustering, or the N value recommended by TopN is not selected properly, but the hybrid recommendation is still better than ordinary collaborative filtering.

scholarly journals Applying N-gram Alignment Entropy to Improve Feature Decay Algorithms

2017 ◽  
Vol 108 (1) ◽  
pp. 245-256 ◽  
Author(s):  
Alberto Poncelas ◽  
Gideon Maillette de Buy Wenniger ◽  
Andy Way
Keyword(s):  
Machine Translation ◽  
English Translation ◽  
Data Selection ◽  
Test Set ◽  
Specific Entropy ◽  
Decay Factor ◽  
N Gram ◽  
Training Examples ◽  
Linear Decay

AbstractData Selection is a popular step in Machine Translation pipelines. Feature Decay Algorithms (FDA) is a technique for data selection that has shown a good performance in several tasks. FDA aims to maximize the coverage of n-grams in the test set. However, intuitively, more ambiguous n-grams require more training examples in order to adequately estimate their translation probabilities. This ambiguity can be measured by alignment entropy. In this paper we propose two methods for calculating the alignment entropies for n-grams of any size, which can be used for improving the performance of FDA. We evaluate the substitution of the n-gram-specific entropy values computed by these methods to the parameters of both the exponential and linear decay factor of FDA. The experiments conducted on German-to-English and Czech-to-English translation demonstrate that the use of alignment entropies can lead to an increase in the quality of the results of FDA.

MAIN PROBLEMS OF USING THE FULL POST-EDITING MODEL BASED ON MACHINE LEARNING FOR ENGLISH-KAZAKH TRANSLATION

2021 ◽  
Vol 74 (2) ◽  
pp. 25-31
Author(s):  
D.R. Rakhimova ◽  
◽  
К. А. Zhakypbayeva ◽  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Machine Translation ◽  
English Translation ◽  
Collaborative Work ◽  
Main Idea ◽  
Model Based ◽  
Translation Systems

Machine learning is one of the main branches of artificial intelligence. Its main idea is not only to use an algorithm written by a computer, but also to learn how to solve a problem on your own. Recently, in the field of translation, the issue of using machine learning and its integration with translator fixes has become very relevant. This new direction in professional English translation is called post-edited machine translation (PEMT) or post-edited machine translation (MTPE). Since the collaborative work of man and machine has given good results, this, in turn, sparked interest in post-editing and the development of automated post-editing systems. The article analyzes the advantages, disadvantages of the currently widely used online translation systems from English into Kazakh. The implementation of machine learning requires a large number of corpuses in English and Kazakh. The article contains code, results that allow you to collect corpuses.

Logistics engineering optimization based on machine learning and artificial intelligence technology

2020 ◽  
pp. 1-12
Author(s):  
Suhua Bu
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Optimal Solution ◽  
Engineering Optimization ◽  
Artificial Intelligence Technology ◽  
Important Means ◽  
Practical Effect ◽  
Combined Classifier ◽  
The Internet Of Things

In the era of the Internet of Things, smart logistics has become an important means to improve people’s life rhythm and quality of life. At present, some problems in logistics engineering have caused logistics efficiency to fail to meet people’s expected goals. Based on this, this paper proposes a logistics engineering optimization system based on machine learning and artificial intelligence technology. Moreover, based on the classifier chain and the combined classifier chain, this paper proposes an improved multi-label chain learning method for high-dimensional data. In addition, this study combines the actual needs of logistics transportation and the constraints of the logistics transportation process to use multi-objective optimization to optimize logistics engineering and output the optimal solution through an artificial intelligence model. In order to verify the effectiveness of the model, the performance of the method proposed in this paper is verified by designing a control experiment. The research results show that the logistics engineering optimization based on machine learning and artificial intelligence technology proposed in this paper has a certain practical effect.

scholarly journals RUSSIAN-TO-ENGLISH SIMULTANEOUS HUMAN TRANSLATION OF CAUSE-AND-EFFECT RELATIONS VS. GOOGLE TRANSLATE

2021 ◽  
Author(s):  
Natalya V. Nikulina ◽  
Keyword(s):  
Artificial Intelligence ◽  
Machine Translation ◽  
English Translation ◽  
Semantic Features ◽  
Cause And Effect ◽  
Internet Resources ◽  
Research Material ◽  
Russian Linguistic ◽  
Simultaneous Translation ◽  
Linguistic Means

The paper emphasizes that the study of Google Translate capacities in simultaneous translation might be relevant due to the advances in machine translation based on artificial intelligence technologies. The research material includes transcripts of public speeches and their Russian-to-English translation collected from the Official Internet Resources of the President of Russia [http://kremlin.ru/] as well as Russian-to-English translation of the speeches via Google Translate. The paper analyses structural and semantic features of Russian linguistic means that convey cause-and-effect relations and reveals the ways of simultaneous human and machine interpreting them into English.

scholarly journals Networked Artificial Intelligence English Translation System Based on an Intelligent Knowledge Base and Translation Method Thereof

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Shuping Ren
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Base ◽  
Structure Analysis ◽  
English Translation ◽  
Language Translation ◽  
Translation Method ◽  
Translation System ◽  
Chinese Translation ◽  
Lexical Structure ◽  
Traditional Language

Language translation is often conducted in work and study. Traditional language translation is based on lexical structure analysis. However, natural language is not so standardized, which causes this translation method to have fundamental defects, no matter how much the algorithm is improved. The translation results and human translation will be very different. This paper mainly studies the networked artificial intelligence. The English translation system and translation methods are based on a smart knowledge base. Bringing an example of English-Chinese translation to suggest translations according to the intelligent knowledge base explains in detail the principle of intelligent knowledge-based translation and the advantage of this translation method compared with the traditional translation method based on lexical structure analysis. In the experiment of this paper, when the variance is 2/N, 30/N, 100/N, and 2N, it is the experimental data for an in-depth study. When the variance is 2/N, 30/N, and 100/N, the result is the same as that when the variance is 0.5; the result when the variance is 2N also conforms to the trend in the tables, which is close to the effect of the smoothing algorithm, which verifies the effectiveness of the system in this paper.

scholarly journals Topical issues of legal regulation of artificial intelligence in the implementation of state and municipal service in the Russian Federation

2021 ◽  
Vol 27 (2) ◽  
pp. 160-163
Author(s):  
Ivan N. Melnikov ◽  
Ivan A. Samakov
Keyword(s):  
Artificial Intelligence ◽  
Russian Federation ◽  
Legal Regulation ◽  
Public Authorities ◽  
Municipal Service ◽  
The Public ◽  
Intelligence System ◽  
Artificial Intelligence Technology ◽  
The Russian Federation

This paper discusses the current issues of legal regulation in the field of artificial intelligence in the state and municipal service in the Russian Federation in order to ensure and protect the rights and freedoms of man and citizen. The article highlights the current problems that arise in the implementation of certain state functions, such as – the work of state bodies with citizens' appeals and the lack of regulatory regulation of the use of artificial intelligence technology in this process, the use of which will contribute to meeting the deadlines for working with citizens' appeals, as well as increase the overall level of quality of interaction between citizens and public authorities. Specific measures are proposed for the development of legislation in order to introduce artificial intelligence in solving the problems facing the public authorities. The article formulates the main conclusion regarding the trend of using the artificial intelligence system in the issue under consideration.

Intelligent Evaluation System of Animation Works Based on ELP

2013 ◽  
Vol 756-759 ◽  
pp. 2416-2421
Author(s):  
Jun Li Zhao
Keyword(s):  
Artificial Intelligence ◽  
Digital Media ◽  
Evaluation System ◽  
Comprehensive Evaluation ◽  
Qualitative Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Teachers And Students ◽  
Artificial Intelligence Technology ◽  
E Learning

In digital media area, exchange and evaluation of the animation works has become a prominent problem. In this paper, we develop an intelligent evaluation system of animation works based on E-learning portfolio, which can record students animation works and learning files in digitized form. It achieves a combination of quantitative evaluation and qualitative evaluation using fuzzy comprehensive evaluation and artificial intelligence technology. It can not only generate the scores, but also generate remarks automatically. This will facilitate teachers and students to exchange and evaluate animation works, and improve the quality of evaluation.

scholarly journals Short Text Paraphrase Identification Model Based on RDN-MESIM

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jing Li ◽  
Dezheng Zhang ◽  
Aziguli Wulamu
Keyword(s):  
Artificial Intelligence ◽  
Rapid Development ◽  
Present Stage ◽  
Short Text ◽  
Application Mode ◽  
Service Areas ◽  
Artificial Intelligence Technology ◽  
Data Inquiry ◽  
Novel Model

In the rapid development of various technologies at the present stage, representative artificial intelligence technology has developed more prominently. Therefore, it has been widely applied in various social service areas. The application of artificial intelligence technology in tax consultation can optimize the application scenarios and update the application mode, thus further improving the efficiency and quality of tax data inquiry. In this paper, we propose a novel model, named RDN-MESIM, for paraphrase identification tasks in the tax consulting area. The main contribution of this work is designing the RNN-Dense network and modifying the original ESIM to adapt to the RDN structure. The results demonstrate that RDN-MESIM obtained a better performance as compared to other existing relevant models and archived the highest accuracy, of up to 97.63%.

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