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Author

Faisal Alkhateeb

Bio: Faisal Alkhateeb is an academic researcher from Yarmouk University. The author has contributed to research in topics: SPARQL & RDF. The author has an hindex of 14, co-authored 55 publications receiving 678 citations. Previous affiliations of Faisal Alkhateeb include French Institute for Research in Computer Science and Automation & University of Nice Sophia Antipolis.
Topics: SPARQL, RDF, RDF Schema, Semantic Web, Query language


Papers
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Journal ArticleDOI
TL;DR: This work defines a language, called PRDF (for ''Path RDF'') which extends RDF such that the arcs of a graph can be labeled by regular expression patterns, and provides PRDF with a semantics extending that of RDF, and proposes a correct and complete algorithm which decides the consequence between an RDF graph and a PRDF graph.

168 citations

Journal ArticleDOI
TL;DR: The results show that using polynomial mutation improves the performance of the HS algorithm for most of the used functions.

41 citations

Journal Article
TL;DR: A system for client-side defenses such as browser plug-ins and classification techniques that are adopted in such detection scenarios that has a better detection accuracy that reaches 96% while false positive rate decreased to 4%.
Abstract: Phishing is an online theft of sensitive information that swindles innocent users into disclosing private information such as user names, passwords, and credit card numbers. The reported number of phishing attacks is growing daily, hence, the loss of the resulting damages are escalating. As a result, there is an urgent need for anti-phishing solutions that is arisen by researchers as well as the IT industry worldwide. Although a number of solutions to mitigate phishing attacks have been proposed, yet they still suffer from high false positive and negative results as well as questioning the feasibility of their implementation. In this work, we propose a system for client-side defenses such as browser plug-ins and classification techniques that are adopted in such detection scenarios. The system inspects the HTML pages as an annotated document represented or embedded in XHTML format using RDF annotations. While the proposed solution has been tested using real sites acquired from the World Wide Web and government agencies concerned on the problem , the method has a better detection accuracy that reaches 96% while false positive rate decreased to 4%. The results show a promising findings in the area of phishing detection that requires hand-in-hand collaboration between various banking branches and the country’s central or authorized bank. Additionally, the system notifies the corresponding bank about the phishing web sites, and the bank in turn notifies its clients.

33 citations

Journal ArticleDOI
TL;DR: A new hybrid CS algorithm (CSBHC) that intelligently combines the CS algorithm with the β-hill climbing algorithm, a variation of the Hill climbing algorithm that is capable of reaching better solutions in a shorter time than many popular local search algorithms.

33 citations

Journal ArticleDOI
TL;DR: A conceptual framework for automatic evaluation of accessibility of rich Internet contents, which includes web robot, RIA events controller, WAI-ARIA accessibility specifications, evaluator, and results handler is presented.

33 citations


Cited by
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Journal ArticleDOI

784 citations

Journal ArticleDOI
01 Mar 2015-Robotica
TL;DR: Methods applicable to stationary obstacles, moving obstacles and multiple vehicles scenarios are reviewed, and particular attention is given to reactive methods based on local sensory data, with a special focus on recently proposed navigation laws based on model predictive and sliding mode control.
Abstract: We review a range of techniques related to navigation of unmanned vehicles through unknown environments with obstacles, especially those that rigorously ensure collision avoidance (given certain assumptions about the system). This topic continues to be an active area of research, and we highlight some directions in which available approaches may be improved. The paper discusses models of the sensors and vehicle kinematics, assumptions about the environment, and performance criteria. Methods applicable to stationary obstacles, moving obstacles and multiple vehicles scenarios are all reviewed. In preference to global approaches based on full knowledge of the environment, particular attention is given to reactive methods based on local sensory data, with a special focus on recently proposed navigation laws based on model predictive and sliding mode control.

390 citations

Journal Article
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373 citations

01 Jan 2008
TL;DR: In this special issue, the focus will be on the technical side, although other issues related to knowledge and data engineering for e-Iearning may also be considered.
Abstract: With the advent of the Internet, we are seeing more sophisticated techniques being developed to support e-Iearning. The rapid developme nt of Web-based learning and new concepts like virtual classrooms, virtual laboratories and virtual universities introduces many new issues to be addressed. On the technical side, we need to develop effective e-technologies for supporting distance education. On the learning and management side, we need to consider issues such as new style of learning and different system set-u p requirements. Finally, the issue of standardization of e-Iearning systems should also be considered. In this special issue, our focus will be on the technical side, although other issues related to knowledge and data engineering for e-Iearning may also be considered. Topics: In this special issue, we call for original papers describing novel knowledge and data engineering techniques that support e-Iearning. Preference will be given to papers that include an evaluation of users' experience in using the proposed methods. Areas of interests include, but are not limited to: • Semantic Web technology for e-Iearning • Data modeling (eg., XML) for efficient management of course materials • Searching and indexing techniques to suppo rt effective course notes retrieval • User-centric e-Iearning systems and user interaction management • Profiling techniques to support grading and learning recommendation • Data and knowledge base suppo rt for pervasive e-Iearning • Course material analysis and understanding • Automatic generation of questions and answers • Collaborative communities for e-Iearning

310 citations