Abdullah Wahbeh

The Effect of Stemming on Arabic Text Classification: An Empirical Study

The information world is rich of documents in different formats or applications, such as databases, digital libraries, and the Web. Text classification is used for aiding search functionality offered by search engines and information retrieval systems to deal with the large number of documents on the web. Many research papers, conducted within the field of text classification, were applied to English, Dutch, Chinese, and other languages, whereas fewer were applied to Arabic language. This paper addresses the issue of automatic classification or classification of Arabic text documents. It applies text classification to Arabic language text documents using stemming as part of the preprocessing steps. Results have showed that applying text classification without using stemming; the support vector machine SVM classifier has achieved the highest classification accuracy using the two test modes with 87.79% and 88.54%. On the other hand, stemming has negatively affected the accuracy, where the SVM accuracy using the two test modes dropped down to 84.49% and 86.35%.

Content-based analysis to detect Arabic web spam

Search engines are important outlets for information query and retrieval. They have to deal with the continual increase of information available on the web, and provide users with convenient access to such huge amounts of information. Furthermore, with this huge amount of information, a more complex challenge that continuously gets more and more difficult to illuminate is the spam in web pages. For several reasons, web spammers try to intrude in the search results and inject artificially biased results in favour of their websites or pages. Spam pages are added to the internet on a daily basis, thus making it difficult for search engines to keep up with the fast-growing and dynamic nature of the web, especially since spammers tend to add more keywords to their websites to deceive the search engines and increase the rank of their pages. In this research, we have investigated four different classification algorithms (naïve Bayes, decision tree, SVM and K-NN) to detect Arabic web spam pages, based on content. The three groups of datasets used, with 1%, 15% and 50% spam contents, were collected using a crawler that was customized for this study. Spam pages were classified manually. Different tests and comparisons have revealed that the Decision Tree was the best classifier for this purpose.

On the Design of IT-Enabled Self-Care Systems: A Socio-technical Perspective

Advances in information technology (IT) have resulted in a proliferation of IT-based solution to support the self-care and management for healthy individuals as well as patients with chronic conditions. Despite these advances, the adoption and diffusion of these solutions into practice is limited. The objective of this paper is to enhance adoption and diffusion by providing actionable recommendations for the design of IT systems for self-care. The recommendations are grounded in socio-technical design theory and in an extensive review of self-care literature. The findings indicate that despite the diversity of disease conditions, users, technologies, and implementation environments, IT-solutions for self-care often fail to encompass a holistic socio-technical view. The design of such systems will need to account for the intrinsic and interrelated characteristics of the underlying tasks, actors, technologies, and environment.

Studying and analysing students web search behaviours within three Jordanian universities

The World Wide Web has become a phenomenon. The web is a crucial source of information for almost every person. Peoples with different jobs using the internet to meet their professional needs, and the university students constitute a large segment of those people who use the internet frequently to accomplish their information needs. This research has conducted an investigation to determine how Jordanian university students are using the web, what are the characteristics of queries used when searching the internet, what are the top searched queries, …, etc. All these goals are achieved after extracting different queries and information from these web log files and analysing them. Results have showed that students are interested in topics related to entertainment and society more than topics related to their studies. Students submit short queries consisting of 1, 2, or 3 terms with little usage of different query operators. Unsurprisingly, they use Google as the preferred search engine and Arabic as the preferred search language.

Pen Testing for Web Applications

As many Web applications are developed daily and used extensively, it becomes important for developers and testers to improve these application securities. Pen testing is a technique that helps these developers and testers to ensure that the security levels of their Web application are at acceptable level to be used safely. Different tools are available for Pen testing Web applications; in this paper the authors compared six Pen testing tools for Web applications. The main goal of these tests is to check whether there are any security vulnerabilities in Web applications. A list of faults injected into set of Web pages is used in order to check if tools can find them as they are claimed. Test results showed that these tools are not efficient and developers should not depend solely on them.