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This article describes a multilayer model-based approach for text compression. It uses linguistic information to develop a multilayer decomposition model of the text in order to achieve better compression. This new approach is illustrated for the case of the Arabic language, where the majority of words are generated according to the Semitic root-and-pattern(More)
With the advent of online data, sentiment analysis has received growing attention in recent years. Sentiment analysis aims to determine the overall sentiment orientation of a speaker or writer towards a specific entity or towards a specific feature of a specific entity. A fundamental task of sentiment analysis is sentiment classification, which aims to(More)
The rapid growth of the Internet and other computing facilities in recent years has resulted in the creation of a large amount of text in electronic form, which has increased the interest in and importance of different automatic text processing applications, including keyword extraction and term indexing. Although keywords are very useful for many(More)
Information systems of many organizations are processed through system of interrelated 'C' programs. Since, the 'C' programming language was developed in the early second half of the last century. It couldn't incorporate to facilitate the current day's technology. Therefore, the programs developed based on this are not coping with the advancement of(More)
A fast method of measuring the distribution of furrows can be obtained via the analysis of TV camera images of skin replicas. These replicas are either negative (or direct) or positive. Reflected or transmitted light is used, depending on the type of replica. Each point of the matrix (256×256 pixels) is digitised over 6 bits (64 levels) and treated by a(More)
  • Arafat Awajan
  • 2015
In this paper, we introduce an efficient method to represent Arabic texts in comparatively smaller sizes without losing significant information. The proposed method uses the linguistic features of the Arabic language, mainly its very productive morphology and its richness in synonyms, to reduce the dimension of the document vector and to improve its vector(More)
An efficient method to compress and reduce the dimensionality of Arabic texts using semantic model-based representation of text is introduced. The proposed system creates equivalence classes, where similar words, generated according to the rich productive morphology of the language and based on the stem-root-pattern paradigm, are grouped together and(More)