Refine
Has Fulltext
- yes (25)
Year of publication
- 2011 (25) (remove)
Document Type
- Preprint (11)
- Book article / Book chapter (9)
- Doctoral Thesis (2)
- Book (1)
- Master Thesis (1)
- Review (1)
Keywords
- Quran (7)
- Koran (6)
- Text Mining (6)
- Bayesian classifier (3)
- Textvergleich (3)
- Base text (2)
- Content Management (2)
- Gothenburg model (2)
- Knowledge Management (2)
- Maschinelles Lernen (2)
Institute
- Institut für deutsche Philologie (25) (remove)
Schriftenreihe
Sonstige beteiligte Institutionen
Das Leiden Christi in Farbe: Zur Funktion der Bühnenanweisungen im ‚Donaueschinger Passionsspiel’.
(2011)
Unter den geistlichen Spielen des späten Mittelalters zeichnet sich das ‚Donaueschinger Passionsspiel’ durch den Umfang und die Detailliertheit seiner Regieanweisungen aus. Sie ergänzen den im Dialog abgefassten Haupttext um epische Partien, die bei der Lektüre das imaginäre Bühnengeschehen illustrieren und bei einer Inszenierung in Bewegung umgesetzt werden. Gebärden und Körperhaltungen der Darsteller werden ebenso beschrieben wie ihre Ausstattung, Kostüme und Requisiten, bis hin zu farblichen Einzelheiten. Anknüpfend an die neuere Forschungsdiskussion über die Medialität geistlicher Spiele fragt die Autorin nach der spezifischen Funktion farblicher Regieanweisungen. Wie die Gattung des Spiels zwischen Textualität und Performativität, Theatralität und Ritualität changiert, kommt auch der Farbe ein eigener medialer Status zu, so die These. Die farblichen Regieanweisungen sollen Leser dazu anregen, zunächst einzelne Details, dann konkrete Bilder und schließlich das gesamte Passionsspiel zu imaginieren.
Thomas Naogeorgs ‘Hamanus’ dokumentiert eindrucksvoll, dass die humanistische Antikenrezeption zur Ausbildung einer eigenen frühneuzeitlichen Poetik führt. Der ‘imitatio veterum’ erteilt Naogeorg eine bewusste Absage und entwickelt eine ‘Tragoedia nova’, indem er mit antiken Gattungskonventionen bricht und komische Elemente in eine Tyrannentragödie integriert. Naogeorg begründet seine konzeptionellen Veränderungen mit dem zeitgenössischen Kontext, in dem sein Werk rezipiert werden soll. Diese Orientierung am Zielpublikum schlägt sich ebenso in der deutschen Übertragung des Johannes Chryseus nieder, der Naogeorgs modifiziertes Tragödienkonzept adaptiert, jedoch ohne die poetischen Spezifika zu würdigen.
Jean Pauls Registerbände
(2011)
Die Dissertation befasst sich mit den Registerbänden Jean Pauls. Diese stellen eine komprimierte Fassung der umfangreichen Exzerptbände dar, die auf mehr als 12.000 Seiten vorliegen. Jean Paul ordnet seine Exzerpte unter zuvor ausgewählten Oberbegriffen, und fasst diese in den Registerbänden zusammen.
Hauptgegenstand dieser Arbeit ist die Untersuchung des Phänomens der mündlichen Ver-wendung von im Chat gebräuchlichen akronymischen Kurzformen wie lol und omg im Deut-schen. Da die Chatkommunikation trotz ihrer schriftlichen Realisierung einige Merkmale mündlicher Kommunikation aufweist, scheint eine Integration der zunächst rein graphischen Kürzungen in die gesprochene Sprache außerhalb des Chats nicht abwegig. Darüber hinaus lassen sich in jüngster Zeit sowohl eine Flexibilisierung der Verwendungsweise der Kürzel als auch Wortbildungsprozesse mithilfe der entsprechenden Formen konstatieren. Es handelt sich dabei um ein jugendsprachliches Phänomen; dies gilt vor allem für den Bereich der Wortbildung. In dieser Arbeit werden die Ergebnisse einer empirischen Erhebung der Relevanz sechs gängiger Kürzel und abgeleiteter Formen vorgestellt und interpretiert. Darüber hinaus erfolgt eine Bestandsaufnahme aller analysierten Formen in Standardnachschlagewerken und diversen Wörterbüchern zu den Soziolekten der Jugend- und Internetsprache.
Der Begriff Germanen ist eine Fremdbezeichnung griechisch-römischer Autoren der Antike. Die so bezeichneten Gruppen hatten aber keine gemeinsame germanische Identität. Die Germanen wurden schon in der Antike als mächtige Gegner stilisiert, was wiederum im Mittelalter im Zuge der Staatenbildungen gerne in den schriftlichen Quellen aufgegriffen wurde. Retrospektiv kann keine "Ursprache" oder "Urheimat" der Germanen rekonstruiert werden. In der Archäologie gibt es jedoch aufgrund des Fundmaterials Kulturräume einer materiellen Kultur, die als germanisch interpretiert werden. Diese sind jedoch nicht mit einer "germanischen Ethnie" zu verwechseln.
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 naïve 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.
Computing Generic Causes of Revelation of the Quranic Verses Using Machine Learning Techniques
(2011)
Because many verses of the holy Quran are similar, there is high probability that, similar verses addressing same issues share same generic causes of revelation. In this study, machine learning techniques have been employed in order to automatically derive causes of revelation of Quranic verses. The derivation of the causes of revelation is viewed as a classification problem. Initially the categories are based on the verses with known causes of revelation, and the testing set consists of the remaining verses. Based on a computed threshold value, a naïve Bayesian classifier is used to categorize some verses. After that, using a decision tree classifier the remaining uncategorized verses are separated into verses that contain indicators (resultative connectors, causative expressions…), and those that do not. As for those verses having indicators, each one is segmented into its constituent clauses by identification of the linking indicators. Then a dominant clause is extracted and considered either as the cause of revelation, or post-processed by adding or subtracting some terms to form a causal clause that constitutes the cause of revelation. Concerning remaining unclassified verses without indicators, a naive Bayesian classifier is again used to assign each one of them to one of the existing classes based on features and topics similarity. As for verses that could not be classified so far, manual classification was made by considering each verse as a category on its own. The result obtained in this study is encouraging, and shows that automatic derivation of Quranic verses’ generic causes of revelation is achievable, and reasonably reliable for understanding and implementing the teachings of the Quran.
The question of why the Quran structure does not follow its chronology of revelation is a recurring one. Some Islamic scholars such as [1] have answered the question using hadiths, as well as other philosophical reasons based on internal evidences of the Quran itself. Unfortunately till today many are still wondering about this issue. Muslims believe that the Quran is a summary and a copy of the content of a preserved tablet called Lawhul-Mahfuz located in the heaven. Logically speaking, this suggests that the arrangement of the verses and chapters is expected to be similar to that of the Lawhul-Mahfuz. As for the arrangement of the verses in each chapter, there is unanimity that it was carried out by the Prophet himself under the guidance of Angel Gabriel with the recommendation of God. But concerning the ordering of the chapters, there are reports about some divergences [3] among the Prophet’s companions as to which chapter should precede which one. This paper argues that Quranic chapters might have been arranged according to months and seasons of revelation. In fact, based on some verses of the Quran, it is defendable that the Lawhul-Mahfuz itself is understood to have been structured in terms of the months of the year. In this study, philosophical and mathematical arguments for computing chapters’ months of revelation are discussed, and the result is displayed on an interactive scatter plot.
Given a collection of diverging documents about some lost original text, any person interested in the text would try reconstructing it from the diverging documents. Whether it is eclecticism, stemmatics, or copy-text, one is expected to explicitly or indirectly select one of the documents as a starting point or as a base text, which could be emended through comparison with remaining documents, so that a text that could be designated as the original document is generated. Unfortunately the process of giving priority to one of the documents also known as witnesses is a subjective approach. In fact even Cladistics, which could be considered as a computer-based approach of implementing stemmatics, does not present or recommend users to select a certain witness as a starting point for the process of reconstructing the original document. In this study, a computational method using a rule-based Bayesian classifier is used, to assist text scholars in their attempts of reconstructing a non-existing document from some available witnesses. The method developed in this study consists of selecting a base text successively and collating it with remaining documents. Each completed collation cycle stores the selected base text and its closest witness, along with a weighted score of their similarities and differences. At the end of the collation process, a witness selected more often by majority of base texts is considered as the probable base text of the collection. Witnesses’ scores are weighted using a weighting system, based on effects of types of textual modifications on the process of reconstructing original documents. Users have the possibility to select between baseless and base text collation. If a base text is selected, the task is reduced to ranking the witnesses with respect to the base text, otherwise a base text as well as ranking of the witnesses with respect to the base text are computed and displayed on a bar diagram. Additionally this study includes a recursive algorithm for automatically reconstructing the original text from the identified base text and ranked witnesses.
Learning a book in general involves reading it, underlining important words, adding comments, summarizing some passages, and marking up some text or concepts. Once deeper understanding is achieved, one would like to organize and manage her/his knowledge in such a way that, it could be easily remembered and efficiently transmitted to others. This paper discusses about modeling religious texts using semantic XML markup based on frame-based knowledge representation, with the purpose of assisting understanding, retention, and sharing of knowledge they contain. In this study, books organized in terms of chapters made up of verses are considered as the source of knowledge to model. Some metadata representing the multiple perspectives of knowledge modeling are assigned to each chapter and verse. Chapters and verses with their metadata form a meta-model, which is represented using frames, and published on a web mashup. An XML-based annotation and visualization system equipped with user interfaces for creating static and dynamic metadata, annotating chapters’ contents according to user selected semantics, and templates for publishing generated knowledge on the Internet, has been developed. The system has been applied to the Quran, and the result obtained shows that multiple perspectives of information modeling can be successfully applied to religious texts, in order to support analysis, understanding, and retention of the texts.
Diese Veröffentlichung ist eine Einführung in die syntaktischen Strukturen der deutschen Gegenwartssprache und deckt folgende Gebiete ab: Satzdefinition, Wortarten, Topologie deutscher Sätze, valenzabhängige und -unabhängige Satzglieder (Ergänzungen und Angaben), Funktion und Semantik von Dativ- und Genitivkonstruktionen, Hilfs-, Modal- und Modalitätsverben, Funktionsverbgefüge und verbale Wendungen, reflexive Konstruktionen, komplexe Sätze und Satzglieder, Passivkonstruktionen, Temporalität sowie Modalität.