An auto-indexing method for Arabic text

This work addresses the information retrieval problem of auto-indexing Arabic documents. Auto-indexing a text document refers to automatically extracting words that are suitable for building an index for the document. In this paper, we propose an auto-indexing method for Arabic text documents. This method is mainly based on morphological analysis and on a technique for assigning weights to words. The morphological analysis uses a number of grammatical rules to extract stem words that become candidate index words. The weight assignment technique computes weights for these words relative to the container document. The weight is based on how spread is the word in a document and not only on its rate of occurrence. The candidate index words are then sorted in descending order by weight so that information retrievers can select the more important index words. We empirically verify the usefulness of our method using several examples. For these examples, we obtained an average recall of 46% and an average precision of 64%.     

Bilingual teachers' language strategies: The case of an Arabic–Hebrew kindergarten in Israel

The goal of this study was to investigate the language-teaching strategies used in a bilingual Arabic–Hebrew kindergarten in Israel. We used an ethnographic approach by applying a mixed methods design. The results demonstrate that the language-teaching strategy most frequently used by teachers was flexible bilingualism, through translanguaging that involved code-switching. This is in contrast to traditional instruction using language separation. In the teachers' opinion, translanguaging enables bilingual children to learn their second language efficiently, especially since Arabic is a socially weaker language in Israel, and it encourages children's interactive involvement in the kindergarten.     

Beyond vector space model for hierarchical Arabic text classification: A Markov chain approach

The vector space model (VSM) is a textual representation method that is widely used in documents classification. However, it remains to be a space-challenging problem. One attempt to alleviate the space problem is by using dimensionality reduction techniques, however, such techniques have deficiencies such as losing some important information. In this paper, we propose a novel text classification method that neither uses VSM nor dimensionality reduction techniques. The proposed method is a space efficient method that utilizes the first order Markov model for hierarchical Arabic text classification. For each category and sub-category, a Markov chain model is prepared based on the neighboring characters sequences. The prepared models are then used for scoring documents for classification purposes. For evaluation, we used a hierarchical Arabic text data collection that contains 11,191 documents that belong to eight topics distributed into 3-levels. The experimental results show that the Markov chains based method significantly outperforms the baseline system that employs the latent semantic indexing (LSI) method. That is, the proposed method enhances the F1-measure by 3.47%. The novelty of this work lies on the idea of decomposing words into sequences of characters, which found to be a promising approach in terms of space and accuracy. Based on our best knowledge, this is the first attempt to conduct research for hierarchical Arabic text classification with such relatively large data collection.     

The cognitive profiles of Jordanian students at risk for math disability

The Cattell–Horn–Carroll (CHC) factors of the Woodcock–Johnson (WJ) Arabic Tests of Cognitive Abilities were studied with a group of students at risk of Math Disability (MD) (n50) and average students (n50) between second and fourth grades. Specifically, several statistical analyses were conducted using the seven CHC factors identified by the WJ Arabic Tests and the level of math calculation skills. The two groups were matched on grade, gender, age, and father’s level of education. The findings indicated that average students had higher scores in all tests, but no statistical difference exists between at risk of MD and average groups in terms of Visual-Spatial Thinking or Auditory Processing scores. In addition, the best model for predicting math calculation skills was based on a combined measure of Processing Speed and Short-Term Working Memory factors. Implications of the findings are also discussed.     

征服与被征服——解读“舒欧比亚”

阿拉伯民族及其文化,实际上是由作为征服者的阿拉伯半岛居民与广大被征服地区皈依伊斯兰教的土著居民长期融合的产物。而"舒欧比亚"乃是这个民族融合体中被征服者对征服者特权地位所作出的反应。这种反应在世界史上又是一种罕见的"例外":被征服者不仅接受了征服者的伊斯兰教信仰,而且还接受了后者的语言,尽管前者的文化要比后者先进得多。这也就凸现出伊斯兰教与阿拉伯语本身的某些"优点"。     

Main Features of Mark of Toledo's Latin Qurʾān Translation

Abstract

This article sets out to be a concise account of Mark of Toledo's Qur?ān translation. It will be structured as follows: first, it will provide information about when and in what circumstances it was realised. Second, it will present some examples, which will show Mark's way of translating and transferring form and content of the Qur?ān for his Latin-speaking Christian audience. Mark mostly translates words consistently throughout the text, and also tries to translate words derived from the same Arabic root with root-related Latin words. Moreover, he does not usually try to convey the semantic nuances a word may have, seemingly not paying attention to the context, but translating with a standard, basic meaning of the word. (This observation should be taken as a tendency and not as a rule, as the excursus at the end will illustrate.) Nevertheless, Mark does not violate the grammar of the Latin language. Despite his fidelity to the text, Mark's Christian cultural background sometimes influences the translation. In the conclusion, the features of Mark's translation will be set out in relation to the cultural and political activity of its commissioner, the Archbishop of Toledo Rodrigo Jiménez de Rada.     

Effects of exposure to literary Arabic on reading comprehension in a diglossic situation

Reading difficulties in Arabic in elementary schoolare usually attributed to the diglossia of the Arabiclanguage, whereby the spoken language is totallydifferent from literary Arabic, the language of booksand school instruction. Educators, teachers, andparents still believe that exposure of young Arabicspeakers to literary Arabic in the preschool period isa burden for them, and is not useful. The presentpost hoc study examined the influence of exposure toliterary Arabic of preschool children on their readingcomprehension of literary Arabic stories in grades 1and 2. Participants in the study were 282children, 135 from grade 1 and 147 from grade 2. Ofthe participants, 144 constituted the experimentalgroup, and were exposed to literary Arabic throughouttheir preschool period. The 138 participants of thecontrol group were exposed not to literary but tospoken Arabic during that period. These children weretested for reading comprehension at the end of grade1 and grade 2 and compared with the control group. The results generally indicate better readingcomprehension results for the children who wereexposed to literary Arabic than for the children whowere exposed only to spoken Arabic.     

Experiment on Chinese postgraduates’ recognizing 100 Everyday English adopting “MMOASAPMI”

The purpose of this study was to investigate the memory effects of the postgraduates’ memorizing Everyday English from 30 to 100 using the Natural Numeral Imagery Memory (Method by memorizing the concrete objects associated with the shapes of Arabic numeral to produce marvelous imagination, MMOASAPMI). The results indicated as follows: Firstly, the postgraduates, who applied the MMOASAPMI to memorize and recall the Everyday English from 30 to 100, could recite them well in sequence backward, forward, and randomly. The reaction time of reciting any sentence randomly is no more than 2 seconds. Secondly, it can transform the materials of the short-term memory into long-term memory quickly, and effectively prevent them from the interference of proactive and retroactive inhibition, so it is useful for keeping memorized information with less loss and remaining for a long period. Thirdly, with the materials in strong sequence, large quantities and the difficulty to memorize, it is an extremely effective method for memorizing them. Fourthly, the keys to improving the memory efficiency are the well-storing skills of memory, storing methods, and memory clues.