Lexicography, the art and craft of dictionary-making, is as old as writing. Since its very early stages several thousands of years ago, it has helped to serve basically the every-day needs of written communication among individuals in communities speaking different languages or different varieties of the same language. Two general approaches are distinguished in the craft of dictionary-making: the semasiological and the onomasiological. The former is represented by usually-alphabetical dictionaries as such, i.e. their being inventories of the lexicon, while the latter is manifested in thesauruses. English and Arabic have made use of both approaches in the preparation of their dictionaries, each having a distinct aim ahead. Within the confines of each language, an approach may yield various trends as to, for instance, the arrangement of entries within a dictionary. The present paper aims at distinguishing the various trends in writing dictionaries in both English and Arabic. By so doing, it is hoped that the bases on which variation has relied are arrived at in order to provide the appropriate explanations of how and why differences have followed. To achieve this aim, an expository critical account of the approaches to the compilation of monolingual dictionaries in English and Arabic is presented; reference to bi-lingual dictionaries is going to be made appropriately, however. These trends, or schools, within each approach followed a certain system in compiling its representative dictionaries.
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
... Show MoreAbstract
The curriculum is amodern science which reflects the social philosophy and
what it needs . It searches for amothod that limits the knowledge that the
indiridual gets in the society and the sorts of the culture that suits the enrironment
in which they live. It also clears for them their history and their great in heritance.
It has a great in flunce in their mental growth ,and it teacher the students new
roles in the thin king ,and training then on what they have learned . According to
there points the problem concentrats on the mostimpotant difficulties which facer
thestudents in studing Arabic langnage text-books
In spite of the great care that the text taker but it is full of subjects and studies
w
Chekhov is well known and perceived in Arab countries. His stories and plays are very popular. They translated it into Arabic by different translators from different languages of the world Many of his stories require new translation solutions to achieve partial, if not complete, equivalence. Chekhov's works are a very difficult subject to analyze and interpret, which is explained by the fact that Chekhov's collections are constantly republished in foreign languages. It is impossible to preserve in translation all the elements of the original text containing historical and national details but, of course, the reader should have the impression that they represent the historical and national situation. When translating, it makes sense to prese
... Show MoreSentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina
... Show MoreTHE PROBLEM OF TRANSLATING METAPHOR IN AN ARTISTIC TEXT (ON THE MATERIAL OF RUSSIAN AND ARABIC LANGUAGES)
MR Younus, Al-A'DAB, 2011
T he article deals with the linguistic, cultural, sociolinguistic, functional and stylistic characteristics of the translation of gluttonic discourse text structures within the framework of the Arabic-Russian combination, as well as with the difficulties encountered in interpretation and translation and related to different conditions under which speech is generated in Arabic and Russian-speaking areas.
The linguistic researcher reads a systematic crisis, idiomatic problems within the linguistic term coming to the Arab culture. Where most of them return back to problems of receiving these sciences which are represented by phenomena like the multiplicity linguistic term, disturbance translated idiomatic concept and its duality.
Aims of the research :
1-Initializing new textbooks to form linguistic project and Arabic linguistic theory.
2-Determination adjusted knowledge, concepts of Arabian heritage linguistics subject
3-Observation the causes of disturbance crisis of linguistic term and its relation to
... Show MoreThis article discusses a discussion of trends and patterns of understanding and application of the concept of metaphor to various subjects that may interfere with the perspective of metaphors in translation theory, an attempt was made to use the principles and characteristics of metaphors and their fundamental tradition in translation theory, and to uncover the perspective of considering metaphor as a conceptual process. presenting its merits, since it is still considered an eccentric expression of linguistics.