An Arabic Text-to-Picture Mobile Learning System

Handled devices and software applications are susceptible to ameliorate learning strength, awareness, and career development. Many mobile-based learning applications are obtainable from the market but Arabic learning shortage is not taken in consideration. We conduct an Arabic Text-to-Picture (TTP) mobile educational application which performs knowledge extraction and concept analysis to generate pictures that represent the content of the Arabic text. The knowledge extraction is based on Arabic semantic models cover important scopes for young children and new Arabic learners (i.e., grammar, nature, animals). The concept analysis uses semantic reasoning, semantic rules, and Arabic natural text processing (NLP) tool to identify word-to-word relationships. The retrieval of images is done spontaneously from local repository and online search engine (i.e., Google or Bing). The instructor can select the Arabic educational content, get semi-automatic generated pictures, and use them for explanation. Preliminary results show improvement in Arabic learning strength and memorization.qscienc

Illustrations Generation Based On Arabic Ontology For Children With Intellectual Challenges

Digital devices and computer software have the prospect to help children with intellectual challenges (IC) in learning capabilities, profession growth, and self-consciousness living. However, most tools and existing software applications that these children utilize are prepared without observance of their particular deficiency. We conduct an Arabic ontology-based learning system that presents automatically illustrations to characterize the content of stories for children with IC in the state of Qatar. We utilize different mechanisms in order to produce these illustrations which comprise: Arabic natural language processing, animal domain-based ontology, word-to-word based relationship extraction, automatic online search-engine querying. The substantial purpose of our proposed system is to ameliorate children with IC the educational, comprehension, perception, and reasoning through the generated illustrations.qscienc

An Arabic mobile educational system

Digital devices and computer software can assist children in improving their learning capabilities and comprehension skills. However most of these items are built without taking into consideration the effective needs and background of Arab children. We propose in this paper an Arabic-based mobile educational system that processes natural questions, extract pertinent answers from animal domain ontology, and illustrate pictures automatically. It combines the transformation of natural language questions into SPARQL queries and finds solutions for multi-phased based questions. In order to process questions, different phases are carried out which include extracting concepts from the Arabic questions, determining the pattern, extraction of word-to-word relationships, extracting knowledge from the ontology, and finding answers through direct or indirect linked data. The aim of our proposed system is to generate substantial pedagogic answers, for asked questions in the natural language, in a specific domain.Scopu

A survey on educational ontologies and their development cycle

Nowadays, the grid of Internet has demonstrated to be plentiful and tremendous data source of information, where diverse domains can be reached and mined. Semantic web is part of the Internet grid where knowledge is provided and has a predefined sense. People can use the big quantity of accessible information for entertainment, exploring knowledge, and learning. In this paper, we provide a survey of educational ontologies, their development life cycle, and the tools used for their implementation. The classification outcomes are beneficial not only for practicality purposes but also for building educational ontologies and their reusability, since it provides a framework for selecting the suitable methodology to be used in specific context, depending also on the requirements of the application itself. IFIP International Federation for Information Processing 2016.Scopu

An e-learning mobile system to generate illustrations for Arabic text

Smart devices applications can assist children in improving their learning capabilities and comprehension skills. However most applications are built without taking into consideration the effective needs and background of Arab children and youth. They are somehow incompatible with their local environment. We propose in this paper an Arabic-based mobile educational system that displays illustrations automatically to characterize Arabic stories' contents. In order to generate these illustrations, different phases are carried out which include processing of Arabic texts, extraction of word-to-word relationships, building and accessing an educational ontology and usage of Internet search engines. The aim of our system is to improve the Arab children educational skills to grasp Arabic vocabulary and grammar using multimedia with a portable smart device which includes observation, comprehension, realization, and deduction. Children will then be able to continue learning outside the limited time of their schools and from any location with enabled Wi-Fi connectivity. Preliminary results show that the system enhances the learners' comprehension, deduction and realization. 2016 IEEE.Scopu

Using fringes for minimal conceptual decomposition of binary contexts

International audienceExtracting knowledge from huge data in a reasonable time is still a challenging problem. Most real data (structured or not) can be mapped to an equivalent binary context, with or without using a scaling method, as for extracting associations between words in a text, or in machine learning systems. In this paper, our objective is to find a minimal coverage of a relation ${\mathcal R}$ with formal concepts. The problem is known to be NP-complete.1 In this paper, we exploit a particular difunctional relation embedded in any binary relation ${\mathcal R}$, the fringe of ${\mathcal R}$, to find an approximate conceptual coverage of ${\mathcal R}$. We use formal properties of fringes to find better algorithms calculating the minimal rectangular coverage of binary relation. Here, a formal context is considered as a binary relation. By exploiting some background on relational algebra in the present work, we merge some results of Belohlavek and Vichodyl,2 using formal concept analysis with previous results obtained by Kcherif et al.3 using relational algebra. We finally propose decomposition algorithms based on the relational formalization and fringe relation

An arabic ontology-based learning system for children with intellectual challenges

Children with intellectual challenges (IC) are growing up with extensive exposure to computer technology. Computer software and assistive devices have the potential to help these children in education, career development, and independent living. However, most of the software, tools and web sites that these children interact with are designed without consideration of their special needs, making these elements less effective or completely inaccessible for them. This paper proposes an assistive education system that dynamically generates multimedia tutorials for children with IC in the state of Qatar. We use several techniques to generate the tutorials which include: Arabic text processing, entities relationship extraction, multimedia-based ontology, and online retrieval of multimedia contents. The main aim of our system is to enhance those children learning capabilities, understanding, communications, thinking and memorization skills through multimedia.Qatar National Research Fund under its award NPRP 09-052-5-003Scopu

A Pictorial Mobile Application for Improving Communication Skills in Non-Verbal Autism

It is estimated that as many as 25 percent of individuals living with autism spectrum disorders are non-verbal. That is, they cannot functionally communicate with others using their voice. Despite that substantial fraction, we still know very little about these individuals, their abilities, and their needs. "We still know very little about the cognitive capabilities of nonverbal people with autism, and how best to help them learn to communicate," said Geri Dawson, Ph.D., Autism Speaks chief science officer. Non-verbal people with autism are usually unable to communicate normally using natural languages. They can, however, learn to communicate through specific symbols and images. Special education instructors have adopted this method of communication to teach non-verbal people with autism. They introduce the symbols and images to them through different methodologies. This learning process appeared to be effective but it is very long. The process is carried out manually and requires a lots of times, dedication, and resources. The instructors should find the materials in different formats and circumstances. They should repeat the lessons several times and normally in a face-to-face framework. We propose in this paper a mobile-based application that allows non- verbal people with autism to learn and communicate with their surroundings using a smart device. They can then be taught to use specific symbols and images through the smart mobile phones. They can form simple words and sentences to express their feelings and needs. The application is flexible and allows the addition of new contents very easily. To assess the progress of the users, different exercises and puzzles are proposed. These allow the users to improve their skills and to continue learning outside the classrooms

A Pictorial Mobile Application for Improving Communication Skills in Non-Verbal Autism

It is estimated that as many as 25 percent of individuals living with autism spectrum disorders are non-verbal. That is, they cannot functionally communicate with others using their voice. Despite that substantial fraction, we still know very little about these individuals, their abilities, and their needs. "We still know very little about the cognitive capabilities of nonverbal people with autism, and how best to help them learn to communicate," said Geri Dawson, Ph.D., Autism Speaks chief science officer. Non-verbal people with autism are usually unable to communicate normally using natural languages. They can, however, learn to communicate through specific symbols and images. Special education instructors have adopted this method of communication to teach non-verbal people with autism. They introduce the symbols and images to them through different methodologies. This learning process appeared to be effective but it is very long. The process is carried out manually and requires a lots of times, dedication, and resources. The instructors should find the materials in different formats and circumstances. They should repeat the lessons several times and normally in a face-to-face framework. We propose in this paper a mobile-based application that allows non- verbal people with autism to learn and communicate with their surroundings using a smart device. They can then be taught to use specific symbols and images through the smart mobile phones. They can form simple words and sentences to express their feelings and needs. The application is flexible and allows the addition of new contents very easily. To assess the progress of the users, different exercises and puzzles are proposed. These allow the users to improve their skills and to continue learning outside the classrooms

Automatic diacritics restoration for modern standard Arabic text

In this paper, the problem of missing diacritic marks in most of Arabic written resources is investigated. Our aim is to implement a scalable and extensible platform to automatically restore missing diacritic marks for Modern Standard Arabic text. Different rule-based and statistical techniques are proposed. These include: morphological analyzer-based, maximum likelihood estimate, and statistical n-gram models. Diacritization accuracy of each technique was evaluated based on Diacritic Error Rate (DER) and Word Error Rate (WER). The proposed platform includes helper tools for text preprocessing and encoding conversion. It yielded a WER of 7.1% and DER of 3.9%. When the case ending was ignored, the platform yielded a WER and DER of 5.1% and 2.7%, respectively. 2016 IEEE.Scopu