Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett, Rafael Mosquera, Sara Hincapié Monsalve, Thom Vaughan, Damian Stewart, Malte Ostendorff, Idris Abdulmumin, Vukosi Marivate, Shamsuddeen Hassan Muhammad, Atnafu Lambebo Tonja, Hend Al-Khalifa, Nadia Ghezaiel Hammouda, Verrah Akinyi Otiende, Tack Hwa Wong, Jakhongir Saydaliev, Melika Nobakhtian, Muhammad Ravi Shulthan Habibi, Chalamalasetti Kranti, Carol Muchemi, Khang Nguyen, Faisal Muhammad Adam, Luis Frentzen Salim, Reem Alqifari, Cynthia Jayne Amol, Joseph Marvin Imperial, Ilker Kesen, Ahmad Mustafid, Pavel Stepachev, Leshem Choshen, David Anugraha, Hamada Nayel, Seid Muhie Yimam, Vallerie Alexandra Putra, My Chiffon Nguyen, Azmine Toushik Wasi, Gouthami Vadithya, Rob Van Der Goot, Lanwenn ar C’horr, Karan Dua, Andrew Yates, Mithil Bangera, Yeshil Bangera, Hitesh Laxmichand Patel, Shu Okabe, Fenal Ashokbhai Ilasariya, Dmitry Gaynullin, Genta Indra Winata, Yiyuan Li, Juan Pablo Martínez, Amit Agarwal, Ikhlasul Akmal Hanif, Raia Abu Ahmad, Esther Adenuga, Filbert Aurelian Tjiaranata, Weerayut Buaphet, Michael Anugraha, Sowmya Vajjala, Benjamin L Rice, Azril Hafizi Amirudin, Jesujoba Oluwadara Alabi, Srikant Panda, Yassine Toughrai, Bruhan Kyomuhendo, Daniel Ruffinelli, Akshata, Manuel Goulão, Ej Zhou, Ingrid Gabriela Franco Ramirez, Cristina Aggazzotti, Konstantin Dobler, Jun Kevin, Quentin Pagès, Nicholas Andrews, Nuhu Ibrahim, Mattes Ruckdeschel, Amr Keleg, Mike Zhang, Casper Rufaro Muziri, Saron Samuel, Sotaro Takeshita, Kun Kerdthaisong, Luca Foppiano, Rasul Dent, Tommaso Green, Ahmad Mustapha Wali, Kamohelo Makaaka, Vicky Feliren, Inshirah Idris, Hande Celikkanat, Abdulhamid Abubakar, Jean Maillard, Benoît Sagot, Thibault Clérice, Kenton Murray, Sarah K. K. Luger. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

This survey presents a comprehensive review of Large Language Models (LLMs) developed for the Arabic language and its dialects. It categorizes models by architecture (encoder-only, decoder-only, and encoder-decoder) and by linguistic form, including Classical Arabic, Modern Standard Arabic, and Dialectal Arabic. We analyze monolingual, bilingual, and multilingual models, evaluating their performance on tasks such as sentiment analysis, named entity recognition, and question answering. The survey also assesses model openness, considering factors like access to source code, training data, weights, and documentation. Our findings highlight a concentration of resources on MSA, a lack of diverse dialectal datasets, and limited transparency across many models. This work offers the first systematic comparison of openness and linguistic coverage in Arabic LLMs and outlines key challenges and research opportunities to support more inclusive, reproducible, and representative Arabic NLP.

Prompt engineering has rapidly emerged as a critical skill for effective interaction with large language models (llMs). However, the cognitive and neural underpinnings of this expertise remain largely unexplored. This paper presents findings from a cross-sectional pilot fMRI study investigating differences in brain functional connectivity and network activity between experts and intermediate prompt engineers. Our results reveal distinct neural signatures associated with higher prompt engineering literacy, including increased functional connectivity in brain regions such as the left middle temporal gyrus and the left frontal pole, as well as altered powerfrequency dynamics in key cognitive networks. These findings offer initial insights into the neurobiological basis of prompt engineering proficiency. We discuss the implications of these neurocognitive markers in Natural Language Processing (NLP). Understanding the neural basis of human expertise in interacting with LLMs can inform the design of more intuitive human-AI interfaces, contribute to cognitive models of LLM interaction, and potentially guide the development of AI systems that better align with human cognitive workflows. This interdisciplinary approach aims to bridge the gap between human cognition and machine intelligence, fostering a deeper understanding of how humans learn and adapt to complex AI systems.

Mispronunciation detection and diagnosis (MDD) is a core component of computer-assisted pronunciation training (CAPT), which aims to provide opportunities for second language learners (L2) to learn and practice their speaking skills. Arabic is one of the most widespread languages in the world, with more than 422 million speakers. It is the language of the Holy Quran, which increases the importance of learning Arabic. Most existing Arabic MDD systems focus on learning-based techniques rather than state-of-the-art deep-learning methods. Most existing Arabic MDD systems are primarily relying on traditional learning techniques. However, integrating Transformer-based algorithms into the system is crucial, as it can significantly enhance the accuracy, efficiency, and overall performance of the Arabic MDD systems. This paper introduces an Arabic MDD system using transformer-based techniques for non-native learners of spoken Arabic language to enhance their learning of Arabic and help non-native speakers practice their pronunciation skills. The study focuses on detecting mispronunciation phonemes and analyzing these pronunciation errors, by identifying the type of each error, whether it was insertion, deletion, or substitution error. To train the MDD system, we constructed a speech dataset for native and non-native Arabic speakers. The performance evaluation was obtained based on the phoneme recognition and MDD performance, and we achieved a phoneme error rate of 3.1%, 80.8%, and 91.3% for diagnosis accuracy and detection accuracy, respectively. Additionally, we conducted a human perceptual test to assess human proficiency in detecting pronunciation errors and compare their evaluations with automatic verification. The automatic verification surpassed human verification, achieving a detection accuracy of 97.0% and a diagnosis accuracy of 80.4%.

Automatic Text Simplification (ATS) is one of the major Natural Language Processing (NLP) tasks, which aims to help people understand text that is above their reading abilities and comprehension. ATS models reconstruct the text into a simpler format by deletion, substitution, addition or splitting, while preserving the original meaning and maintaining correct grammar. Simplified sentences are usually evaluated by human experts based on three main factors: simplicity, adequacy and fluency or by calculating automatic evaluation metrics. In this paper, we conduct a meta-evaluation of reference-based automatic metrics for English sentence simplification using high-quality, human-annotated dataset, NEWSELA-LIKERT. We study the behavior of several evaluation metrics at sentence level across four different sentence simplification models. All the models were trained on the NEWSELA-AUTO dataset. The correlation between the metrics’ scores and human judgements was analyzed and the results used to recommend the most appropriate metrics for this task.

Large Language Models (LLMs) have shown superb abilities to generate texts that are indistinguishable from human-generated texts in many cases. However, sometimes they generate false, incorrect, or misleading content, which is often described as “hallucinations”. Quantifying and analyzing hallucination in LLMs can increase their reliability and usage. While hallucination is being actively studied for English and other languages, and different benchmarking datsets have been created, this area is not studied at all for Arabic. In our paper, we create the first Arabic dataset that contains 10K of generated sentences by LLMs and annotate it for factuality and correctness. We provide detailed analysis of the dataset to analyze factual and linguistic errors. We found that 25% of the generated sentences are factually incorrect. We share the dataset with the research community.

Professions in the areas of Science, Technology, Engineering, and Mathematics (STEM) are the driver for technological innovation and economic growth. However, Educators are facing challenges creating awareness and excitement for STEM careers to attract young students to the field. Due to teenagers' wide interest in mobile technologies, our camp used smartphones as a context to teach programming. We organized a one-week summer camp targeting middle and high school students. The camp introduced mobile application development using basic web technologies (HTML, CSS, JavaScript). Therefore, this paper presents an experience report describing our approach and the most innovative activities that were applied. Our evaluation of the camp includes surveys and the students' projects to measure the success of the camp in reaching its objectives. The results show that the students enjoyed the camp, learned and used the main concepts in their projects, and became interested in the field. We also discuss the limitations and future improvements based on our experience and observations.

With the increasing number of predatory publishers that involves charging publication fees to authors without providing proper peer-review or editorial refereeing to qualify papers for publication; The need for a web-based system that involves the participation of authors and researchers in reporting such publishers is becoming a must.

Sentiment Analysis (SA) is an active research area nowadays due to the tremendous interest in aggregating and evaluating opinions being disseminated by users on the Web.SA of English has been thoroughly researched; however research on SA of Arabic has just flourished.Twitter is considered a powerful tool for disseminating information and a rich resource for opinionated text containing views on many different topics.In this paper we attempt to bridge a gap in Arabic SA of Twitter which is the lack of sentiment lexicons that are tailored for the informal language of Twitter.We generate two lexicons extracted from a large dataset of tweets using two approaches and evaluate their use in a simple lexicon based method.The evaluation is performed on internal and external datasets.The performance of these automatically generated lexicons was very promising, albeit the simple method used for classification.The best F-score obtained was 89.58% on the internal dataset and 63.1-64.7% on the external datasets.

App Inventor (AI) for Android is a block-based programming environment that enables nonprogrammers to create fully functional mobile applications for Android phones by dragging and dropping code blocks. Since the launch of AI, many improvements were applied to it, which aimed to increase its effectiveness in promoting programming education for beginners. In our workshop, which targeted high school female students, we taught mobile programming using the improved version of AI2 (a free cloud-based tool). Thus, in this paper, we will describe our experience in using AI2 in our workshop, how it helped in our teaching method and discuss the improvements and limitations we observed over the previous version of the tool. We will also show the activities provided to the students and the mobile apps that were created using AI2. The final apps as well as the survey results showed how effective was the workshop and how the improved version of AI has enhanced the teaching process.

Internet of Things (IoT) devices are becoming commercially available, from Amazon Echo to simple Amazon Dash buttons; the realization of such devices which responds to end users' actions are now at the reach of developers' hands due to the existence of cheap electronic kits and plethora of Web APIs.

Usability of government mobile applications is essential for the effective use by end users. However, the lack of mobile application usability checklist tailored to the governmental sector is a problem that needs to be tackled. In this paper we report our experience in drafting a heuristic checklist, based on previous usability metrics, tailored for government mobile applications and apply it on a sample of Saudi government mobile applications.

This paper describes the design and implementation of a web-based system and web service for decoding and coloring Arabic text. The decoding of Arabic text is done by analyzing and identifying attached affixes (prefixes and suffixes), particle and silent letters of the selected text based on the sentence morphological structure. Our proposed system, which we called ArCode, is a combination of color-coding technique, Transliteration and text-to-speech technologies that creates an educational tool for learning Arabic language. It also provides web services for developers who want to integrate the system in their own applications.

Open Government Data (OGD) initiatives and more specifically OGD portals have increased rapidly worldwide since the late 2000's, including the Gulf Cooperation Council (GCC) countries. A comprehensive analysis of the capabilities and potential of these initiatives particularly for the GCC members from a technical perspective is currently missing from existing research literature. To address this gap, this paper aims at assessing the technical maturity of OGD Portals for each of the six countries of the GCC through investigating their services and characteristics. Our study results illustrate the current technical quality of the surveyed portals and spotlight the work that needs to be done to reach a full technical maturity in order to make public data truly open and readily available for citizens, researchers, and innovation in general.

Due to the limitation of the available tools that enhance math education for visually impaired students, this paper proposes the design of an authoring tool that helps math teachers produce accessible learning materials for linear equations in the form of 3D models. The proposed tool will focus on producing 3D models of linear equation graphs printed in predefined plates with proper Braille captioning.

This paper describes the design and development of a Lightweight Language Learning Management System (L3MS) using Mobile Web technologies and APIs. The system aims at allowing language students to view and download learning content on their own mobile phones and to perform interactive tasks designed by the teacher. The usability of the developed system was evaluated and the results revealed a generally positive attitude towards using the system and high usability rates from both the teacher and students.

Most kindergarten students spend the majority of their day in schools, so it is important to provide them with the tools and techniques that help them develop intellectually and educationally. In this poster we propose a system that facilitates kindergarten educational process by utilizing a Humanoid robot called NAO. NAO robot will be programmed to support fun learning through providing many activities and games. The robot system will provide quizzes to test the student's understanding. It will also enable the teacher to continuously review the student's progress through an application interface installed on his/her computer.

This paper presents a proposed solution to enhance web browsing accessibility of Google Glass for Visually Impaired People (VIP). It presents the design of Google Glass Application that allows VIP to browse the Web more easily. The proposed app will be installed on Google Glass and will include a proxy service that synchronizes with the Glass through the Internet. The app will direct any requested webpage to the proxy, which adapts the requested webpage in accordance with the user's preferences. This app will allow visually impaired users to benefit from the Glass features and, most importantly, the Glass audio system.

Achieving web accessibility has become a global aim nowadays, especially with the significant inclusion of the Internet in our daily lives. There exist different accessibility evaluation methods that support web developers and designers during websites' development life cycle, and each has different benefits and drawbacks. However, many studies show that there is a continued lack of equality between disabled and non-disabled people in benefitting from the web, especially with the prolonged growth of web development standards and techniques, which raises a demand for continuous improvement in web accessibility evaluation methods in order to gain reliable results. Given this demand, our paper investigates the advancements in web accessibility evaluation methods for the past five years (2011-2015). The results reveal a lack of significant evolution of these evaluation methods. Based on our findings, more efforts are required for enhancing accessibility evaluation techniques in order to achieve better web accessibility.

Tracking is a process that captures knowledge of the path of an object's movement and its current location. This paper proposes an ultra-wideband (UWB) indoor tracking system for blind people in a high interference environment such as facilities with communication equipment. To the best of our knowledge, our proposed system is the first that offers two features (1) server-based tracking, in which the administrator can get the current position and the path of the blind person in question; and (2) situation awareness, in which the blind person can get voice information about existing and surrounding places. The system has shown satisfactory results when it was used and evaluated by some blind participants.

Recently, subjectivity and sentiment analysis of Arabic has received much attention from the research community. In the past two years, an enormous number of references in the field have emerged compared to what has been published in previous years. In this paper, we present an updated survey of the emerging research on subjectivity and sentiment analysis of Arabic. We also highlight the challenges and future research directions in this field.

The user location information represents a core dimension as understanding user context is a prerequisite for providing human-centered services that generally improve quality of life. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task due in part to the expected various objects (such as walls and people) that reflect and disperse signals. In this paper, we survey the related work in the field of indoor positioning by providing a comparative analysis of the state-of-the-art technologies, techniques, and algorithms. Unlike previous studies and surveys, our survey present new taxonomies, review some major recent advances, and argue on the area open problems and future potential. We believe this paper would spur further exploration by the research community of this challenging problem space.

With the ever-increasing role played by technological innovations in countries' development and economic growth, governments and educational institutes are keen to encourage and promote computing and engineering education among its young generations. In a developing country such as Saudi Arabia, we observed a certain knowledge gap in truly comprehending the true essence of computing as a science field. High school computing curriculum mainly tackles training students to use various applications and shallow programming instructions. Consequently, we observed that many college freshmen students chose the computing field (or avoid it) based on the misconception that it is mainly about dealing with Office applications or ‘fixing computers’. To change this misconception and attract students who are in a critical phase of choosing their future path and inform them off why they should consider computing as an option, we organized a two weeks summer camp. The summer camp focused on two interesting topics among teenagers, namely: mobile technologies and robotics. Accordingly, this paper presents an experience report describing our approach and evaluation from teaching a summer camp for high school girls using App Inventor and LEGO Mindstorm NXT.

A "Completely Automated Public Turing test to tell Computers and Humans Apart" (CAPTCHA) is a widely used technique in many websites for protecting their online services from malicious users. Yet, end-user perceptions related to the complexity of CAPTCHA varies based on the visual properties of a CAPTCHA. In this paper we present an empirical pilot study that employs eye tracking to measure the complexity of CAPTCHA with different properties using three metrics: fixation count, fixation duration and task completion. Our initial results reveal that with high CAPTCHA complexity, the fixation count and fixation duration increase, on the other hand, the task completion decrease. The approach we used can be incorporated with other metrics for providing an additional technique to measure the usability of CAPTCHAs.

Corpora have opened up many new areas of research in the linguistic domain, which would never been possible without them. Moreover, corpora have proved their usefulness not only in the linguistic domain but also in other domains, such as medical, economic, legal, pharmacological, etc. English is considered to have the richest language resources in most of these domains, while Arabic reveals a gap in most of them. This paper tries to fill the gap in the pharmacological domain, especially for drugs, by constructing the first Arabic drug corpus, which is composed of 202 drugs, each drug is saved in a text file with UTF-8 character encoding. The corpus was manually annotated with four-entity types: generic (for drug's generic name), brand for (trade names), chemical formula and class (for drug classes).

Touch screen devices are used daily in a variety of tasks, such as sending emails and typing notes. These devices usually come equipped with soft keyboards where their design needs to strike a careful balance to meet user needs. In this empirical study, we employed eye tracking techniques on four variants of soft keyboards to explore Users Experience (UX) while using different soft keyboard layouts, and discuss possible reasons for this differences and design implications for better typing performance.

This paper serves to introduce an initial haptic based system for teaching handwriting of Arabic letters to students with visual impairments. The proposed system provides full and partial guidance through haptic playback. In addition, the system automatically evaluates student progress.

This paper describes a computer science summer camp workshop designed for high school girls. High school girls have a common misconception about computer science and information technology fields; this misconception leads to choosing or avoiding the computing discipline mistakenly. The workshop aimed at increasing awareness of computer science among high school girls, clarifying the misconception, and attracting potential students to choose the computing field for their college major. The main contributions of this paper include thorough evaluation of the workshop's impact using pre and post surveys, as well as lessons learned after conducting the workshop.

According to World Health Organization (WHO), in June, 2012 there were 285 million Visually Impaired People (VIP) around the world. Unfortunately, many face difficulties when browsing and getting information from the Internet especially when using traditional methods. In our paper, we aim at taking advantage of context-aware computing to assist VIP with contextualized web pages. We propose an integrable proxy service to minimize VIP's browsing problems and make it more effective. This service can reorganize the requested Web page content according to the user's preferences, so screen readers would not read content that is not of interest to the user. The result of the proxy was evaluated using two approaches: (1) manual inspection and (2) user testing. In the first experiment, 64% of the 50 converted websites got satisfactory results. In the second experiment, five VIP have tested the output of our service and expressed their general satisfaction with it.

DBpedia knowledge base extracts structured information from Wikipedia pages and makes them accessible on the Web. In the past few years, the efforts of DBpedia internationalization (i18n) were effective and many localized DBpedia are now available to access as DBpedia chapters. The Arabic chapter of DBpedia is not yet available, thus the collaboration between both Arab contributors and DBpedia community is needed to fulfill this mission. In this paper, we discuss DBpedia internationalization current state and provide recipes for creating Arabic DBpedia.

In this poster we aim to recount our effort to raise the awareness of mobile and web developers of the concept of Mobile Widgets through a series of workshops. The workshops were attended by information technology students and professional developers. The poster will briefly define the concept of Mobile Widgets as a W3C recommendation, though a yet unpopular recommendation, and report our effort to make Mobile Widgets well known among developers via workshops specifically designed to interest web and mobile developers alike. The importance of the workshop arises from our belief that popularity among developers will result in mobile operating system vendors? support.

In the past few years, a great attention has been paid for digitizing and indexing cultural heritage resources, particularly Arabic manuscripts. Most Arabic manuscript libraries use traditional metadata for describing its resources. They also provide little or no support for annotation. In this paper we propose a system that extends one of the popular Arabic manuscripts libraries, Makhtota maintained by King Saud University, with a document level semantic metadata. The system will also propose the use of a manual annotation mechanism to enrich manuscripts' pages with linked data.

Text-To-Speech synthesizer (TTS) is a computer-based program which allows text to be pronounced using a humanoid voice. Basically, judgment of TTS programs quality is measured by two criteria: (1) similarity to human voice (i.e. naturalness), and (2) ability to be understood (i.e. intelligibility). There are many useful usages of TTS programs in our daily routines; among them is the facilitation of accessing text over mobile phones by visually impaired people. In order to check the correctness and naturalness of TTS programs used in mobile phones, this paper provides an initial comparison of two different speech engines used in current mobile phones (Android and iOS) based on a set of criteria. Our results show that the Arabic speech engine used in iOS produced more natural and understandable voice compared to Android, even though Android speech engine was better in many criteria compared to iOS engine.

With the increasing interest in social media, sentiment Analysis has become a hot topic in the research community. This is due to the important applications that can be derived from analyzing people opinions. Although there are many tools that were designed to extract sentiments, they can be only used for Latin Scripts. This presents the need for giving more interest to Arabic sentiment analysis research. In fact, earlier research in this field is limited and most of them focused on formal Arabic. For that reason, the paper attempts to investigate the problems of analyzing informal Arabic sentiments. To explore these problems, an experiment based on a dictionary look-up process was carried out on Twitter Arabic messages. As a result of this experiment, a classification of the encountered problems is provided. This classification can be considered as a step toward designing efficient sentiment Analysis tools for informal Arabic. In addition, highlighting these problems may encourage researchers to contribute more in this field.

In this paper, we will discuss a new approach for peer assessment based on the well-known Prisoners' Dilemma game. The approach uses collaborative translation activity assisted by prisoner's dilemma game. The result shows an overall satisfaction of the new knowledge gained in this activity, where more than 70% of the students acknowledge that the activity increased their understanding of the subject knowledge.

Lexical competence lies at the heart of language learning, it is an essential element for acquiring reading, writing and communication proficiency. Although vocabulary instruction is an essential part in a language classroom, research suggests that learners still lack necessary lexical competence in word knowledge. In this paper we propose an educational software tool, called LEXI, which aims to enhance learners' lexical competence using ontologies. Ontologies provide a model which is capable of representing lexical semantics in a way which explicate meat-linguistic information. Adopting such a model will provide an environment which supports learners in grasping the meaning of words, and thus improving their lexical competence.

Visual impairment is one of the disabilities that could injure people congenitally or adventitiously. The number of individuals who suffer from visual impairment is increasing rapidly. Therefore, there is an urgent need to develop assistive technologies that aid blind people. Our proposed system aims to provide an assistive technology for blind and visually impaired individuals by exploiting the power of smart phones, which are existing, popular, and often used by blind individuals. Our proposed system provides a novel navigation system that operates on smart phones and provides a route to any destination in a building from the user's current position.

With the rapid growth of social networks, Twitter provides a dynamic and powerful social tool for discussing political issues. In fact, in Saudi Arabia, discussing political issues over Twitter has become a popular phenomenon among young Saudi citizens. The purpose of this paper is to conduct a pilot study to understand the underlying social structure of youth Saudi citizens' interaction and discussion of political issues over Twitter using the theory of Social Network Analysis (SNA). The result of SNA reveals relevant differences in the patterns of interconnection among different political topics. It also provides an insight into sociological characteristics of modern political issues in Saudi Arabia.

With the increasing use of mobile phones to access the web, many public and private entities have followed the trend of designing a mobile version of their websites without basing their design decisions on vivid design approaches. This issue can be attributed to the lack of design practices and recommendation tailored to specific genres of websites. In this paper, we propose a design approach for developing mobile government websites based on their provided functionality. We also describe the framing of the approach and apply it on a set of Saudi government websites.

Sentiment analysis is the process of identifying the polarity of sentiments held in opinions found in pieces of text and classifying them as positive, negative or neutral. In this paper, we propose the implementation of a sentiment analysis tool that is conducted over text found in Arabic new media including web forums, comments on newspaper articles and other websites with evaluative content. The expected input of the tool, which is informal Colloquial Arabic, is characterized to be of highly non-structured nature and subject to trends used to express sentiments. Our solution is a novel technique that merges the area of human computation with the task of natural language processing.

This paper presents two approaches for building ontologies to represent Quranic words based on the field of componential analysis. The first approach is a class-based ontology and the second is an instance-based ontology. Both approaches are described in details along with the result of the comparison.

In this paper, we propose the building of ontologies from Arabic Wikipedia. Our solution relies on a hybrid approach where Wikipedia categories' hierarchy will serve as a backbone of the ontology, and then they are refined and extended by semantic relations extracted from Wikipedia articles infoboxes and hyperlinks. Moreover, we plan to investigate the effectiveness of using each approach independently to build the required ontology.

Due to the large amount of information available on the web that is not necessarily true or believable, credibility of web information is becoming an increasingly important area to understand. Recently, most research has been available to develop automatic measures for web information credibility in languages such as Japanese, Germen and English websites. Unfortunately, there is no research for the credibility of Arabic web content.

To achieve the vision of the semantic web, web pages need to be transformed into a machine-processable form to enable computers understand them. This vision can be reached by using a common technique of web page annotation. Web page annotation is considered one of the effective techniques for relating text to knowledge representation artifacts. In this paper we present an Arabic semantic annotation tool called AraTation for semantically annotating Arabic News content on the web. This tool is constructed using the Java programming language and OWL ontologies to produce RDF metadata for web pages. The RDF standard will make the annotated Arabic web pages reusable and machine processable on the web. By using the AraTation tool, we can contribute to the vision of the semantic web and open the field for Arabic semantic web research.

There are many Arabic educational resources on the web scattered in personal websites and forums, and created by members of the community. Searching for such resources using regular search engines is not an easy task. In this paper we describe "Marifah", an Arabic Learning Object Repository with recommendation capabilities, created for hosting Arabic learning objects and serving the needs of the Arabic educational community. The repository has integrated advanced features that cannot be fulfilled using well-know search engines.

IEEE-LOM is a well-known metadata standard for describing learning resources. However, many problems are associated with this kind of representation, which include the number of fields to be filled and the amount of time needed to fill them. To overcome this hurdle, we propose the use of cheap unstructured metadata to create structured semantic metadata, this metadata is called folksonomy. In this paper we show an approach that uses folksonomy tags to create structured metadata using semantic web technologies. The generated folksonomic metadata are then evaluated against a human expert annotation.

Finding good keywords to describe resources is an on-going problem. Typically, we select such words manually from a thesaurus of terms, or they are created using auto-matic keyword extraction techniques. Folksonomies are an increasingly well-populated source of unstructured tags describing Web resources. This article explores the value of the folksonomy tags as a potential source of keyword metadata by examining the relationship between folksonomies, community produced annotations, and keywords extracted by machines. The experiment has been carried out in two ways: subjectively, by asking two human indexers to evaluate the quality of the generated keywords from both systems; and automatically, by measuring the percentage of overlap between the folksonomy set and machine generated keywords set. The results of this experiment show that the folksonomy tags agree more closely with the human generated keywords than those automatically generated. The results also showed that the trained indexers pre-ferred the semantics of folksonomy tags compared to keywords extracted automatically. These results can be considered as evidence for the strong relationship of folksonomies to the human indexer’s mindset, demonstrating that folksonomies used in the del.icio.us bookmarking service are a potential source for generating semantic metadata to annotate Web resources.

Abstract People with visual disabilities face many difficulties and barriers when using computers and the Internet. Such people need the help of IT developers to create adaptive technologies that facilitate their interaction with the computers and Internet. This paper presents the design and implementation of an Arabic Braille environment (ABE). The paper also exposes to the reader the ABE's functionality and unique features. The ABE is designed to facilitate Arabic‐speaking visually impaired people interaction with computers, as well as helping sighted users to communicate with the visually impaired. Copyright © 2003 John Wiley & Sons, Ltd.