The article is devoted to the Russian-Arabic translation, a particular theory of which has not been developed in domestic translation studies to the extent that the mechanisms of translation from and into European languages are described. In this regard, as well as with the growing volumes of Russian-Arabic translation, the issues of this private theory of translation require significant additions and new approaches. The authors set the task of determining the means of translation (cognitive and mental operations and language transformations) that contribute to the achievement of the most equivalent correspondences of such typologically different languages as Russian and Arabic. The work summarizes and analyzes the accumulated experience of modern Russian linguists, Arabists (Belkin V.M., Gabuchan G.M., Grande B.M., Finkelberg N.D., Frolov V.D., etc.) and representatives of the Arabic classical linguistic school (Ibn Jinni, Sibawayh, etc.) in determining the carrier of word-formation meaning. The purpose of the study is designated as the description of the role of this category in achieving equivalence in the pair of Russian and Arabic. The lexical-semantic group of tools and instruments was considered as a material. These lexemes, both in Russian and Arabic, have an acceptable frequency, cover various stylistic registers and are formed by a relatively limited set of formants, interlingual correspondences of which can be established and compared. For the first time, on the material of this lexico-semantic group, a systemic interlingual correlation of the series of word-building formants in Russian and Arabic is revealed. The authors draw conclusions about the category of the word-formation model as a key one in the algorithm of translation activity, as well as about the specific linguistic signs of the equivalence of the Arabic-Russian translation (full transfer of the real meaning of the motivating base, the coincidence of the rhythm of the derived Arabic word with a model, the correspondence of the derivative to the grammatical categories contained in the model).
Abstract Lanɡauaɡes, like humans, need communication and interaction to prosper. One of the ways for a language to flourish is to borrow words from other languages. The southern regions of Iran and the coastal countries of Persian Gulf have had strong cultural relations since old times, with language being a dimension of these relations. With their land being geographically located in the realm of Islamic civilization and being Muslims, Baloch people have had strong connections with the Arab world and the Arabic language.Thus, many Arabic words have made their ways into Balochi language either directly or indirectly through persian language. Since each language has its own unique sound structure, these loanwords have undergone ph
... Show MoreThis article presents and explores the theoretical aspect in the use of Arab Islamic theme by the western writers to obtain and achieve individual motives. In this study the model for the theory of Arab presence in Andalusia , through the book entitled “ Alhamra” by the English writer Washington Erving ,was analyzed.
The most important results in this research: the success of the author in the employment of the Islamic history in the formation of the first American legend, Columbus legend, through the selection of the right thoughts to establish his American National theory. The author compared between the Andalusia experience and the Arab occupation to Spain and the American conquest of the new
... Show MoreLoanwords are the words transferred from one language to another, which become essential part of the borrowing language. The loanwords have come from the source language to the recipient language because of many reasons. Detecting these loanwords is complicated task due to that there are no standard specifications for transferring words between languages and hence low accuracy. This work tries to enhance this accuracy of detecting loanwords between Turkish and Arabic language as a case study. In this paper, the proposed system contributes to find all possible loanwords using any set of characters either alphabetically or randomly arranged. Then, it processes the distortion in the pronunciation, and solves the problem of the missing lette
... Show MoreThis research focuses on the services provided by news websites (IMN, Youm7, Huffington Post Arabic) to its audience of Internet users, as well as materials posted through its pages, trying to monitor and explain them to identify their types & features, and it›s functions, whether informational or non-informational, to know the technical potential of each of the news sites, with the entry of the latest technology information. The research used the analysis method to achieve the research objectives within the period from 1/1 to 31/1/2017. The researchers used the content analysis tool as a research tool to analyze the news sites and to know the services they provide through their pages. The research was divided into three parts, the
... Show MoreAccording to grammarians In ( نإ) and Itha (اذإ) are conditionals and sometimes they may be used interchangeably. However, when they are mentioned in the Holy Qur’an, they have their own specific use. This paper attempts to investigate their meanings in the source language as well as investigate their translations and find out any differences or similarities. The translations that are adopted in this research are as follows: Pickthall, Al-Hilali & Khan, and Shakir.
In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N
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