Importance of Arabic language stemming algorithm is not less than that of other languages stemming in Information Retrieval (IR) field. Lots of algorithms for finding the Arabic root are available and they are mainly categorized under two approaches which are light (stem)-based approach and root-based approach. The latter approach is somehow better than the first approach. A new root-based stemmer is proposed and its performance is compared with Khoja stemmer which is the most efficient root-based stemmers. The accuracy ratio of the proposed stemmer is (99.7) with a difference (1.9) with Khoja stemmer.

 Most of the propositions, after the Arabic letter reached a position of integrity and proficiency, the calligrapher turned to the production of calligraphic formations in various aesthetic and expressive forms, investing the spiritual energies in what these calligraphic compositions show in artistic paintings. It carries a lot of meanings that are embodied in linear formations, and in order to reach these expressions and know the effective positions of space, this research is concerned with studying these technical treatments. The first chapter included the research problem, which included a question about the effectiveness of space in the linear painting, the importance of research and the temporal and spatial boundaries. As for the s

Calculating similarities between texts that have been written in one language or multiple languages still one of the most important challenges facing the natural language processing. This work offers many approaches that used for the texts similarity. The proposed system will find the similarity between two Arabic texts by using hybrid similarity measures techniques: Semantic similarity measure, Cosine similarity measure and N-gram ( using the Dice similarity measure). In our proposed system we will design Arabic SemanticNet that store the keywords for a specific field(computer science), by this network we can find semantic similarity between words according to specific equations. Cosine and N-gram similarity measures are used in order t

     It is doubtless that the sexual place has some common indicators due to the masculine and feminine bodies which may be natural or deviated (homosexual). The female has an act of voice in the imaginary masculine place whereas the male has an act of image recognized in the parental mind in both the secular and sacred place. Those places create different limits and perceptions according to the auditory and visual readings in search of identity, text and body in the feminine dramatic text.

    The research includes four chapters; the first, the methodological framework, involves the problem which is centralized in the following enquiry: What is the relationship between the place and the term of

Honorifics are linguistic expressions which maintain social as well as religious respect to other people. They are linguistic techniques which express politeness to other interlocutors. Semantically speaking, honorifics are of two types: al-Laqab (title) and al-Kuniya (teknonyms) following a specific word order. They form part of the Arab recognitions and are mold into their social and communicative competence.

      The study focuses upon religious and regional honorifics which convey deference and respect. It assumes that religious and cultural recognitions play vital roles in formulating and embedding the sense of honorifics. It is hypothesized that Arab people express respect to religious personalitie

Stemming is a pre-processing step in Text mining applications as well as it is very important in most of the Information Retrieval systems. The goal of stemming is to reduce different grammatical forms of a word and sometimes derivationally related forms of a word to a common base (root or stem) form like reducing noun, adjective, verb, adverb etc. to its base form. The stem needs not to be identical to the morphological root of the word; it is usually sufficient that related words map to the same stem, even if this stem is not in itself a valid root. As in other languages; there is a need for an effective stemming algorithm for the indexing and retrieval of Arabic documents while the Arabic stemming algorithms are not widely available.

    Keywords provide the reader with a summary of the contents of the document and play a significant role in information retrieval systems, especially in search engine optimization and bibliographic databases. Furthermore keywords help to classify the document into the related topic. Keywords extraction included manual extracting depends on the content of the document or article and the judgment of its author. Manual extracting of keywords is costly, consumes effort and time, and error probability. In this research an automatic Arabic keywords extraction model based on deep learning algorithms is proposed. The model consists of three main steps: preprocessing, feature extraction and classification to classify the document

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