Attar, F. A., and K. Shaalan, "Enablers and Barriers of Knowledge Spiral: A Case Study", The 11th International Knowledge Management in Organizations Conference (KMO '16), Germany, 28 July, 2016. Abstracta52-attar.pdf

Knowledge Management (KM) and knowledge sharing (KS) have become crucial tasks for both Middle Managers and Top Managers of many organizations, especially those who highly rely on the type of knowledge which is difficult to transfer from one person to another, or what is called “Tacit Knowledge”. The objective of this case study is to review the practical knowledge transfer techniques, the main motivators and demotivators of a tacit knowledge transfer process, and the measures that can be taken to overcome the demotivation factors. Siemens is chosen for this case study because it has been recently rated as one of the top Knowledge-Management-driven companies. We present here our own observations on some of the KM practices that Siemens strives to implement in its branches in the Middle East countries and the barriers which are challenging such practices.

Dali, H., and K. Shaalan, "Knowledge Sharing Through E-Government Portal", The 11th International Knowledge Management in Organizations Conference (KMO '16), Germany, 25 July, 2016. Abstracta34-dali.pdf

The advent of technology has changed the way of government to communicate with its stakeholders by incorporating the notion of e-government based on web-portal. These web-portals whereas identified successful in communicating with the stakeholders also played a vital role in sharing and managing knowledge. Based on this notion, this article is concerned with the role of e-government portal in sharing knowledge and the way through which this portal increases the efficiency of entire public sector. In the same instance, the K-ACT model of internet portal is analyzed to identify the features that make a web-portal best and perfect. In this article, we conducted a literature review and focused our attention on analyzing the e-government portals of four countries i.e. China, Hong Kong, Beijing and Turkish Municipalities. For the analysis and comparison purposes, the checklist of K-ACT model is used. The findings revealed that the e-government portal of these countries is not fully matched with the features as described in K-ACT, which ultimately affect the knowledge management and sharing practices in the region. Therefore, recommendations are made to improve the existing portal for knowledge sharing so that citizens can take more knowledge benefits from the e-government portals.

Samra, R. A., and K. Shaalan, "Exploring Chaotic Performance in Projects and its Relationship with Knowledge Creation Process", The 11th International Knowledge Management in Organizations Conference (KMO '16), Germany, 25 July, 2016. Abstracta27-samra.pdf

In this study the researcher is focusing on the performance of the project. During the life cycle of projects managers are striving to forecast the future performance of the project according to the historical patterns of performance. Irregular performance and randomness are representing chaotic performance periods in project’s life. The study proposes five propositions. The first proposition is that Manager have different conscious perceptions about accepted levels of order and chaos in their project performance. The second proposition is that Knowledge Creation Process has different characteristics in chaotic perceived projects and order perceived projects. The third proposition is that managers have different prioritization of knowledge assets from which they create new knowledge for chaotic performance projects. The fourth proposition is that Sources of knowledge creation differ according to the context of project performance. The fifth proposition is that Assets used for knowledge creation during chaotic performance periods differ according to managers’ tendency to innovate. This study is a qualitative analysis of secondary data that comes from literature review and primary data that comes from interviews with experts and project managers. The researcher investigated four styles of knowledge creation during chaotic performance periods; experiential knowledge creation style, innovative knowledge creation style, precautions and risk minimization knowledge creation style, and specialty based knowledge creation style. Conclusions and recommendations are provided to project managers on which knowledge assets are leading to innovative knowledge creation.

Nabhan, A. R., and K. Shaalan, "Keyword identification using text graphlet patterns", Natural Language to Information Systems: 21st International Conference on Applications of Natural Language to Information Systems (NLDB 2016), Berlin , Springer, 2016. Abstractpaper_published.pdf

Keyword identification is an important task that provides useful information for NLP applications including: document retrieval, clustering, and categorization, among others. State-of-the-art methods rely on local features of words (e.g. lexical, syntactic, and presentation features) to assess their candidacy as keywords. In this paper, we propose a novel keyword identification method that relies on representation of text abstracts as word graphs. The significance of the proposed method stems from a flexible data representation that expands the context of words to span multiple sentences and thus can enable capturing
of important non-local graph topological features. Specifically, graphlets (small subgraph patterns) were efficiently extracted and scored to reflect the statistical dependency between these graphlet patterns and words labeled as keywords. Experimental results demonstrate the capability of the graphlet patterns in a keyword identification task when applied to MEDLINE, a standard research abstract dataset.

Siddiqui, S., A. A. Monem, and K. Shaalan, "Sentiment Analysis in Arabic", Natural Language to Information Systems: 21st International Conference on Applications of Natural Language to Information Systems (NLDB 2016), Berlin , Springer, 2016. Abstractsentiment_analysis_in_arabic.pdf

The tasks that falls under the errands that takes after Natural Language Processing approaches includes Named Entity Recognition, Information Retrieval, Machine Translation, and so on. Wherein Sentiment Analysis utilizes Natural Language Processing as one of the way to locate the subjective content showing negative, positive or impartial (neutral) extremity (polarity). Due to the expanded utilization of online networking sites like Facebook, Instagram, Twitter, Sentiment Analysis has increased colossal statures. Examination of sentiments helps organizations, government and other association to extemporize their items and administration in view of the audits or remarks. This paper introduces an Innovative methodology that investigates the part of lexicalization for Arabic Sentiment examination. The system was put in place with two principles rules– “equivalent to” and “within the text” rules. The outcomes subsequently accomplished with these rules methodology gave 89.6 % accuracy when tried on baseline dataset, and 50.1 % exactness on OCA, the second dataset. A further examination shows 19.5 % in system1 increase in accuracy when compared with baseline dataset.

Alomari, K. M., T. R. Soomro, and K. Shaalan, "Mobile Gaming Trends and Revenue Models", Trends in Applied Knowledge-Based Systems and Data Science, Switzerland, Springer, 2016. Abstractmobile_gaming_trends_and_revenue_models.pdf

The study tries to find out the most important features in building games based on the grossing. The study is limited to fifty iPhone games that have achieved top grossing in the USA. The game features were extracted from a previous study [1] and classified through ARM funnel into five groups (“A”, “R”, “M”, “AR”, and “RM”). The paper follows CRISP-DM approach under SPSS Modeler through business and data understanding, Data preparation, model building and evaluation. The researcher uses Decision Tree model since the features have closed value i.e. (Yes/No) on the grossing weight. The study reached to the most important 10 features out of 31. These features are important to build successful mobile games. The study emphasizes on the availability of (Acquisition, Retention and Monetization) elements on every successful game and if any is missed, will lead to the failure of the game.

Hassan, L. K. A., T. Rahim, and K. Shaalan, "Business Continuity Perspective: A Study of IT Enabled Services", International Journal of Computer Applications, vol. 142, issue 4, pp. 20-26, 2016. Abstracthassan-2016-ijca-909749.pdfWebsite

The increasing trends of technological immersion into the businesses lead towards many form of indecisions. The business world required certain planning to overcome the problems and recovery from many disasters accommodating to Information Technology. Businesses required running their tasks with the inclusion of the knowledge and IT within the organization. The respective report is concerned to approach the Information Technology meditation to examine the business continuity in the certain IT disasters. A mixed methodology approach for collection of the data is used in the study in which quantitative and qualitative methods are considered. The outcomes of the study will assist the IT-enabled organization to plan their business activities to abide the misery from disasters.

Al-Emran, M., H. M. Elsherif, and K. Shaalan, "Investigating Attitudes Towards the Use of Mobile Learning in Higher Education", Computers in Human Behavior, vol. 56, pp. 93-102, 2016. Abstractkshaalan_attitude_study.pdfWebsite

Mobile learning (M-learning) has become an important educational technology component in higher education. M-learning makes it possible for students to learn, collaborate, and share ideas among each other with the aid of internet and technology development. However, M-learning acceptance by learners and educators is critical to the employments of M-learning systems. Attitudes towards M-learning technology is an important factor that helps in determining whether or not learners and educators are ready to use M-learning. Such attitudes will serve to identify strengths and weaknesses and facilitate the development of the technology infrastructure. This paper aims at exploring students and educators' attitudes towards the use of M-learning in higher educational universities within Oman and UAE; two neighboring countries in the Arab Gulf region. To serve this purpose, two survey questionnaires were conducted: one for students and another for educators. The participants of this study are 383 students and 54 instructors from five universities. Different factors have been examined to test where there is a significant difference among students and educators' attitudes towards the use of M-learning, such as gender, age, country, level of study, smartphone ownership, major in terms of students and age, country, academic rank, academic experience and smartphone ownership in terms of educators. Findings revealed significant differences among the students’ attitudes towards M-learning with regard to their smartphone ownership, country and age. Furthermore, results indicated that M-learning can be one of the promising pedagogical technologies to be employed in the higher educational environments within the Arab Gulf countries.

Atia, S., and K. Shaalan, "Increasing the Accuracy of Opinion Mining in Arabic", The International Conference on Arabic Computational Linguistics (ACLing), Cairo, Egypt, 18 April, 2015. Abstractopinionminacling2015.pdf

Opinion Mining is a raising research field of interest, with its different applications derived by market needs
to analyze product reviews or to assess the public opinion, for political reasons, during presidential campaigns. In this paper, we address an approach for improving accuracy of Opinion Mining in Arabic. In order to conduct our study we need Arabic linguistic resources for opinion mining. Investigating the available resources we found that the OCA corpus is available and sufficient to prove our approach. Experimental results showed that applying different parameters of the machine learning classifiers on the OCA corpus leads to increasing the accuracy of the Arabic Opinion Mining.

Al-Chalabi, H., S. Ray, and K. Shaalan, "Semantic Based Query Expansion for Arabic Question Answering Systems", The International Conference on Arabic Computational Linguistics (ACLing), Cairo, Egypt, 17 April, 2015. Abstractqeacling2015.pdf

Question Answering Systems have emerged as a good alternative to search engines where they produce the desired information in a very precise way in the real time. However, one serious concern with the Question Answering system is that despite having answers of the questions in the knowledge base, they are not able to retrieve the answer due to mismatch between the words used by users and content creators. There has been a
lot of research in the field of English and some European language Question Answering Systems to handle this issue. However, Arabic Question Answering Systems could not match the pace due to some inherent difficulties with the language itself as well as due to lack of tools available to assist the researchers. In this paper, we are
presenting a method to add semantically equivalent keywords in the questions by using semantic resources. The experiments suggest that the proposed research can deliver highly accurate
answers for Arabic questions.