@unpublished{Nassourou2012,
  author    = {Nassourou, Mohamadou},
  title     = {Towards a Knowledge-Based Learning System for The Quranic Text},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-70003},
  year      = {2012},
  abstract  = {In this research, an attempt to create a knowledge-based learning system for the Quranic text has been performed. The knowledge base is made up of the Quranic text along with detailed information about each chapter and verse, and some rules. The system offers the possibility to study the Quran through web-based interfaces, implementing novel visualization techniques for browsing, querying, consulting, and testing the acquired knowledge. Additionally the system possesses knowledge acquisition facilities for maintaining the knowledge base.},
  subject      = {Wissensbanksystem},
  language  = {en}
}
@unpublished{Nassourou2010,
  author    = {Nassourou, Mohamadou},
  title     = {Understanding the Vex Rendering Engine},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-51333},
  year      = {2010},
  abstract  = {The Visual Editor for XML (Vex)[1] used by TextGrid [2]and other applications has got rendering and layout engines. The layout engine is well documented but the rendering engine is not. This lack of documenting the rendering engine has made refactoring and extending the editor hard and tedious. For instance many CSS2.1 and upcoming CSS3 properties have not been implemented. Software developers in different projects such as TextGrid using Vex would like to update its CSS rendering engine in order to provide advanced user interfaces as well as support different document types. In order to minimize the effort of extending Vex functionality, I found it beneficial to write a basic documentation about Vex software architecture in general and its CSS rendering engine in particular. The documentation is mainly based on the idea of architectural layered diagrams. In fact layered diagrams can help developers understand software's source code faster and easier in order to alter it, and fix errors. This paper is written for the purpose of providing direct support for exploration in the comprehension process of Vex source code. It discusses Vex software architecture. The organization of packages that make up the software, the architecture of its CSS rendering engine, an algorithm explaining the working principle of its rendering engine are described.},
  subject      = {Cascading Style Sheets},
  language  = {en}
}
@unpublished{Nassourou2011,
  author    = {Nassourou, Mohamadou},
  title     = {Using Machine Learning Algorithms for Categorizing Quranic Chaptersby Major Phases of Prophet Mohammad's Messengership},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-66862},
  year      = {2011},
  abstract  = {This paper discusses the categorization of Quranic chapters by major phases of Prophet Mohammad's messengership using machine learning algorithms. First, the chapters were categorized by places of revelation using Support Vector Machine and na{\"i}ve Bayesian classifiers separately, and their results were compared to each other, as well as to the existing traditional Islamic and western orientalists classifications. The chapters were categorized into Meccan (revealed in Mecca) and Medinan (revealed in Medina). After that, chapters of each category were clustered using a kind of fuzzy-single linkage clustering approach, in order to correspond to the major phases of Prophet Mohammad's life. The major phases of the Prophet's life were manually derived from the Quranic text, as well as from the secondary Islamic literature e.g hadiths, exegesis. Previous studies on computing the places of revelation of Quranic chapters relied heavily on features extracted from existing background knowledge of the chapters. For instance, it is known that Meccan chapters contain mostly verses about faith and related problems, while Medinan ones encompass verses dealing with social issues, battles…etc. These features are by themselves insufficient as a basis for assigning the chapters to their respective places of revelation. In fact, there are exceptions, since some chapters do contain both Meccan and Medinan features. In this study, features of each category were automatically created from very few chapters, whose places of revelation have been determined through identification of historical facts and events such as battles, migration to Medina…etc. Chapters having unanimously agreed places of revelation were used as the initial training set, while the remaining chapters formed the testing set. The classification process was made recursive by regularly augmenting the training set with correctly classified chapters, in order to classify the whole testing set. Each chapter was preprocessed by removing unimportant words, stemming, and representation with vector space model. The result of this study shows that, the two classifiers have produced useable results, with an outperformance of the support vector machine classifier. This study indicates that, the proposed methodology yields encouraging results for arranging Quranic chapters by phases of Prophet Mohammad's messengership.},
  subject      = {Koran},
  language  = {en}
}