Islam Elkabani

Smodels with CLP and Its Applications: A Simple and Effective Approach to Aggregates in ASP

In this work we propose a semantically well-founded extension of Answer Set Programming (ASP) with aggregates, which relies on the integration between answer set solvers and constraint logic programming systems. The resulting system is efficient, flexible, and supports form of aggregation more general than those previously proposed in the literature. The system is developed as an instance of a general framework for the embedding of arbitrary constraint theories within ASP.

SMODELS A : a system for computing answer sets of logic programs with aggregates

In [2], we presented a system called - for computing answer sets of logic programs with aggregates. The implementation of - relies on the use of an external constraint solver (ECLiPSe) to deal with aggregate literals and requires some modifications to the answer set solver used in the experiment (Smodels). In general, the system is capable of computing answer sets of arbitrary programs with aggregates, i.e., there is no syntactical restrictions imposed on the inputs to the system. This makes - different from dlvA (built BEN/5/23/04) [1], which deals with stratified programs only. - , however, is based on a semantics that does not guarantee minimality of answer sets. Furthermore, our experiments with - indicate that the cost of communication between the constraint solver and the answer set solver proves to be significant in large instances.

Homophily-Based Link Prediction in The Facebook Online Social Network: A Rough Sets Approach

Abstract Online social networks are highly dynamic and sparse. One of the main problems in analyzing these networks is the problem of predicting the existence of links between users on these networks: the link prediction problem. Many studies have been conducted to predict links using a variety of techniques like the decision tree and the logistic regression approaches. In this work, we will illustrate the use of the rough set theory in predicting links over the Facebook social network based on homophilic features. Other supervised learning algorithms are also employed in our experiments and compared with the rough set classifier, such as naive Bayes, J48 decision tree, support vector machine, logistic regression, and multilayer perceptron neural network. Moreover, we studied the influence of the “common groups” and “common page likes” homophilic features on predicting friendship between users of Facebook, and also studied the effect of using the Jaccard coefficient in measuring the similarity between users’ homophilic attributes compared with using the overlap coefficient. We conducted our experiments on two different datasets obtained from the Facebook online social network, where users in each dataset live within the same geographical region. The results showed that the rough set classifier significantly outperformed the other classifiers in all experiments. The results also demonstrated that the common groups and the common page likes features have a significant influence on predicting the friendship between users of Facebook. Finally, the results revealed that using the overlap coefficient homophilic features provided better results than that of the Jaccard coefficient features.

Smodels with CLP—A Treatment of Aggregates in ASP

Many practical systems have been recently proposed to support execution of Answer Set Programming (ASP) [13,7,1,10]. Our objective is to introduce different types of aggregates in ASP. Database languages (e.g., SQL) use aggregate functions—e.g., sum, count, and max—to obtain summary information from a database. Aggregates have been shown to significantly improve compactness and clarity of programs in various flavors of logic programming [9,6]. We expect to gain similar advantages from the introduction of aggregations in ASP.

An Interactive Workspace for Helping the Visually Impaired Learn Linear Algebra

In this paper an interactive workspace designed to help visually impaired students practice the fundamentals of linear algebra is introduced. Unlike most of the approaches, this interactive workspace aims at enhancing math manipulation abilities for students who are visually impaired, mainly dealing with linear algebra expression that requires more complicated techniques in accessing. Read-expression, Hide-Row/Column, and Text-Tools are examples of techniques that the workspace implements. Such techniques are invoked by hot access keys which in turn with audio feedback allow the user to navigate and edit the linear algebra expression, access its elements especially matrices, find the solution and save it for further review and edit. The methodology followed is to list all the operations required in Linear Algebra. Then the tasks which require visual abilities were isolated and implemented in the framework.

Dynamic single node failure recovery in distributed storage systems

Abstract With the emergence of many erasure coding techniques that help provide reliability in practical distributed storage systems, we use fractional repetition coding on the given data and optimize the allocation of data blocks on system nodes in a way that minimizes the system repair cost. We selected fractional repetition coding due to its simple repair mechanism that minimizes the repair and disk access bandwidths together with the property of un-coded repair process. To minimize the system repair cost, we formulate our problem using incidence matrices and solve it heuristically using genetic algorithms for all possible cases of single node failures. We then address three practical extensions that respectively account for newly arriving blocks, newly arriving nodes and variable priority files. A re-optimization mechanism for the storage allocation matrix is proposed for the first two extensions that can be easily implemented in real time without the need to redistribute original on-node blocks. The third extension is addressed by implementing variable fractional repetition codes which is shown to achieve significant cost reduction. The contributions of the paper are four fold: (i) generating an optimized block distribution scheme among the nodes of a given data center for fixed and variable size blocks; (ii) optimization of storage allocation under dynamic environments with data block arrivals; (iii) optimization of storage allocation with newly added storage nodes; and (iv) generating an effective block distribution scheme among the nodes by accounting for varying priorities among data blocks. We present a wide range of results for the various proposed algorithms and considered scenarios to quantify the achievable performance gains.

Enhancement of Arabic Text Classification Using Semantic Relations of Arabic WordNet

Arabic text classification methods have emerged as a natural result of the existence of a massive amount of varied textual information (written in Arabic language) on the web. In most text classification processes, feature selection is crucial task since it highly affects the classification accuracy. Generally, two types of features could be used: Statistical based features and semantic and concept features. The main interest of this paper is to specify the most effective semantic and concept features on Arabic text classification process. In this study, two novel features that use lexical, semantic and lexico-semantic relations of Arabic WordNet (AWN) ontology are suggested. The first feature set is List of Pertinent Synsets (LoPS), which is list of synsets that have a specific relation with the original terms. The second feature set is List of Pertinent Words (LoPW), which is list of words that have a specific relation with the original terms. Fifteen different relations (defined in AWN ontology) are used with both proposed features. Naive Bayes classifier is used to perform the classification process. The experimental results, which are conducted on BBC Arabic dataset, ‎show that using LoPS feature set improves the accuracy of Arabic text ‎classification compared with the well-known Bag-of-Word feature and the ‎recent Bag-of-Concept (synset) features. Also, it was found that LoPW (especially with related-to relation) improves the classification accuracy compared with LoPS, Bag-of-Word and Bag-of-Concept.

Toward better web accessibility

Web page evaluation systems are needed to evaluate the accessibility of websites. Such evaluation is important so that website administrators can change their websites so people with disabilities would be able to use them. Currently, such systems produce varying results that are not always useful for website administrators. Moreover it is difficult to ascertain for sure to what degree the web pages conform to accessibility guidelines. In this paper, the current state of open-source web accessibility evaluation tools is reviewed. As a result, AChecker, a system that evaluates web page compliance with WCAG 2.0, is identified as the best available. Three types of deficiencies in AChecker are identified, unclear comments, redundancy of errors reporting and lack of automatic or semiautomatic repair. An interactive evaluation tool (IWAET) is developed based on AChecker. The usability of the new system is studied. The study involved a group of web developers with different levels of programming experience and no accessibility knowledge. Both quantitative and qualitative approaches were adopted in usability evaluation. The developed system is compared to AChecker. The results of the evaluation are presented which show clearly the superiority of the new system compared to the currently available systems.

Evolution of Hashtags on Twitter: A Case Study from Events Groups

Twitter is a micro-blogging interactive platform that captured fame due to its simple features that allowed the communication between users. As the interactive communication grew bigger and faster, a feature called Hashtags became very known, famous and recognized by most of users as it acquainted the themes behind the posted tweets. This study focuses on the factors causing people to participate on some trendy hashtags on Twitter online social network. Consequently, these factors affect the evolution of such trendy hashtags over time. In order to study this evolution, a dataset reflecting real tweets from common events occurring between December 2015 and January 2016 were crawled. The reciprocal effect of users’ topological features and activity levels has been studied. Two Influence Measures and one Topological Measure have been introduced in this work. Moreover, other measures available in the literature such as Activity Measures and Centrality Measures have been used. These measures, along with the three newly introduced measures contributed in the determination of the measures that might be influential for a user to attract other users to a certain hashtag. In this work, the focus is on the centrality levels in addition to the activity levels of users participating on the hashtags under study and the effect of those levels on the activity or the membership of other users on same hashtags.

A framework for helping the visually impaired learn and practice math

Visually impaired people usually try to build their careers in areas where the use of mathematics is minimal. This is because learning or practicing mathematics demands highly visual abilities. In this paper, a framework is introduced which will enable visually impaired students to learn and practice mathematics like sighted students. The framework was instantiated successfully to enable visually impaired students to learn and practice linear algebra. An electronic system was developed which was used by visually impaired university students. In addition, an instantiation was implemented to help visually impaired upper elementary and middle school students learn and practice Algebra using either Arabic or English. This instantiation has been implemented as an electronic system and tested for upper elementary students. Encouraging results were reported. Currently work is ongoing to augment it to serve middle school students.