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% Selection : Entry type = PhdThesis
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@PhdThesis{Avgustinova:1997_2,
      AUTHOR = {Avgustinova, Tania},
      TITLE = {Word Order and Clitics in Bulgarian},
      YEAR = {1997},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Department of Slavistics, Computational Linguistics},
      NOTE = {Dissertation in Computational Linguistics and Language Technology, Volume 5}
}

@PhdThesis{Backofen:1994,
      AUTHOR = {Backofen, Rolf},
      TITLE = {Expressivity and Decidability of First-Order Languages over Feature Trees},
      YEAR = {1994},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Technische Fakultät},
      URL = {ftp://lt-ftp.dfki.uni-sb.de/pub/papers/local/kndisco.dvi.Z ftp://lt-ftp.dfki.uni-sb.de/pub/papers/local/kndisco.entry ftp://lt-ftp.dfki.uni-sb.de/pub/papers/local/kndisco.ps.Z},
      ANNOTE = {COLIURL : Backofen:1994:EDF.pdf Backofen:1994:EDF.ps Backofen:1994:EDF.dvi}
}

@PhdThesis{Balari:1993,
      AUTHOR = {Balari, Sergio},
      TITLE = {On the Organization of Knowledge in a Constraint-Based Theory of Grammar},
      YEAR = {1993},
      ADDRESS = {Barcelona},
      SCHOOL = {University of Barcelona}
}

@PhdThesis{Brants:1999,
      AUTHOR = {Brants, Thorsten},
      TITLE = {Tagging and Parsing with Cascaded Markov Models - Automation of Corpus Annotation. Saarbrücken Dissertations in Computational Linguistics and Language Technology, Volume 6.},
      YEAR = {1999},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes},
      URL = {http://www.dfki.de/lt/diss/diss_en.htm},
      ABSTRACT = {This thesis presents new techniques for parsing natural language. They are based on Markov Models, which are commonly used in part-of-speech tagging for sequential processing on the word level. We show that Markov Models can be successfully applied to other levels of syntactic processing. First, two classification tasks are handled: the assignment of grammatical functions and the labeling of non-terminal nodes. Then, Markov Models are used to recognize hierarchical syntactic structures. Each layer of a structure is represented by a separate Markov Model. The output of a lower layer is passed as input to a higher layer, hence the name: Cascaded Markov Models. Instead of simple symbols, the states emit partial context-free structures. The new techniques are applied to corpus annotation and partial parsing and are evaluated using corpora of different languages and domains.}
}

@PhdThesis{Busemann:1990,
      AUTHOR = {Busemann, Stephan},
      TITLE = {Generierung natürlicher Sprache mit Generalisierten Phrasenstrukturgrammatiken},
      YEAR = {1990},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Fachbereich Informatik}
}

@PhdThesis{Busemann:1990_1,
      AUTHOR = {Busemann, Stephan},
      TITLE = {Generierung natürlicher Sprache mit Generalisierten Phrasenstrukturgrammatiken},
      YEAR = {1990},
      NUMBER = {87},
      SERIES = {KIT Report},
      ADDRESS = {Berlin},
      SCHOOL = {Technische Universität Berlin, Fachbereich Informatik}
}

@PhdThesis{De Kuthy:2000,
      AUTHOR = {De Kuthy, Kordula},
      TITLE = {Discontinuous NPs in German},
      YEAR = {2000},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes},
      URL = {http://www.dfki.de/dfkibib/publications/docs/dekuthy-thesis.ps.gz},
      ANNOTE = {COLIURL : Kuthy:2000:DNG.pdf Kuthy:2000:DNG.ps}
}

@PhdThesis{Egg:2000,
      AUTHOR = {Egg, Markus},
      TITLE = {Flexible Semantic Construction: The Case of Reinterpretation},
      YEAR = {2000},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Department of Computational Linguistics}
}

@PhdThesis{Erbach:1997,
      AUTHOR = {Erbach, Gregor},
      TITLE = {Bottom-Up Earley Deduction for Preference-Driven Natural Language Processing},
      YEAR = {1997},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Department of Computational Linguistics},
      URL = {https://www.coli.uni-saarland.de/~erbach/pub/diss/erbach-diss.pdf},
      ABSTRACT = {The thesis discusses the processing of principle-based grammars such as HPSG, with an application to best-first processing for disambiguation, selection of paraphrases and possibly also handling ill-formed input. Grammars are treated as a definite clause programs, to which program transformation and deduction techniques can be applied. In particular, the view of constraint logic programming is adopted, which abstracts away from the handling of constraints (which is regarded as a service provided by the constraint solver) and concentrates on resolution strategies. The contributions of the thesis are the following: A constraint language supporting sorted feature terms, Prolog terms, multi-dimensional inheritance, finite domains, by compilation to Prolog terms. The constraint language has been extended with external constraint solvers for set constraints, LP constraints, guarded constraints. A partial deduction system for compiling a principle-based grammar into a set of grammar rules. Partial deduction can be applied selectively through control information in the program, which makes it possible to do experimental work in order to determine the selection of goals to which partial deduction is best applied in order to bring the greatest performance improvement. Bottom-Up Earley deduction as a deduction system which generalises bottom-up chart parsing to a wider class of grammars/programs than just those with a context-free backbone. Bottom-up Earley deduction is better suited for handling discontinuous constituency than its top-down counterpart, it allows best-first search based on bottom-up information (e.g. tag probabilities), and provides different indexing schemes for different modes of combination of items. The correctness, completeness and termination properties of the algorithm have been shown. A generalised linguistic deduction system, which allows combination of different deduction strategies via control annotations, and which is tightly integrated with the underlying programming language in order to achieve efficiency. A fully incremental algorithm for bottom-up Earley deduction has been specified, which can cope efficiently with a change in the query by re-using intermediate deduction results as much as possible. Augmentation of a definite clause language with preference values. We have discussed how preference values from a variety of sources can be combined.},
      ANNOTE = {COLIURL : Erbach:1997:BED.pdf}
}

@PhdThesis{Fouvry:2003,
      AUTHOR = {Fouvry, Frederik},
      TITLE = {Robust Processing for Constraint-based Grammar Formalisms},
      YEAR = {2003},
      MONTH = {April},
      SCHOOL = {Department of Language and Linguistics, University of Essex},
      ABSTRACT = {This thesis addresses the issue of how Natural Language Processing (NLP) systems using constraint-based grammar formalisms can be made robust, i.e. able to deal with input which is in some way ill-formed or extragrammatical. In NLP systems which use constraint-based grammars the operation of unification typically plays a central role. Accordingly, the central concern of this thesis is to propose an approach to robust unification. The first part of the thesis underlines the importance of robustness in NLP, provides an overview of the sort of phenomena that require it, and reviews the state of the art. From this, it appears that no methods currently exist for robust processing with grammars of any real linguistic sophistication. The class of constraint-based grammars studied here is that based on Typed Feature Logic (TFL), of which Head-Driven Phrase Structure Grammar is the instance chosen for exemplification. The formalism is described in the second part of the thesis. Grammars based on TFL involve the notion of a signature, which defines the kinds of objects (types) assumed to exist in the grammar. Processing typically involves combining information about pieces of the input by unification. From this perspective, the need for robustness can be seen as arising because pieces of the input provide information which is inconsistent with information from other pieces of the input and/or from the grammar. The first inconsistency is tolerated --- it does not violate the grammar --- and processed using robust types which are created by extending the signature to a lattice. Inconsistency with the grammar on the other hand is punished by stripping away the offending information. Weights, added to it on the basis of the grammar, also disappear, thus making the ungrammaticality measurable. The conceptual and formal apparatus for this is developed and exemplified in the third part of the dissertation.}
}

@PhdThesis{Hansen:2002,
      AUTHOR = {Hansen, Silvia},
      TITLE = {The Nature of Translated Text - An Interdisciplinary Methodology for the Investigation of the Specific Properties of Translations},
      YEAR = {2002},
      ADDRESS = {Saarbrücken, Germany},
      SCHOOL = {Institute for Applied Linguistics - Translation and Interpreting, Saarland University}
}

@PhdThesis{Henz:1997,
      AUTHOR = {Henz, Martin},
      TITLE = {Objects in Oz},
      YEAR = {1997},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Fachbereich Informatik},
      ABSTRACT = {The programming language Oz integrates the paradigms of imperative, functional and concurrent constraint programming in a computational framework of unprecedented breadth, featuring stateful programming through cells, lexically scoped higher-order programming, and explicit concurrency synchronized by logic variables. Object-oriented programming is another paradigm that provides a set of concepts useful in software practice. In this thesis we address the question how object-oriented programming can be suitably supported in Oz. As a lexically scoped higher-order language, Oz can express a wide range of object-oriented concepts. We present a simple yet expressive object system, demonstrate its usability and outline an efficient implementation. A central aspect of Oz is its support for concurrent computation. We examine the impact of concurrency on the design of an object system and explore the use of objects in concurrent programming.}
}

@PhdThesis{Koreman:1996,
      AUTHOR = {Koreman, Jacques},
      TITLE = {Decoding Linguistic Information in the Glottal Airflow},
      YEAR = {1996},
      ADDRESS = {Nijmegen},
      SCHOOL = {University of Nijmegen, Department of Language and Speech}
}

@PhdThesis{Krenn:1999,
      AUTHOR = {Krenn, Brigitte},
      TITLE = {The Usual Suspects: Data-Oriented Models for Identification and Representation of Lexical Collocations},
      YEAR = {1999},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes}
}

@PhdThesis{Krenn:2000_3,
      AUTHOR = {Krenn, Brigitte},
      TITLE = {The Usual Suspects: Data-Oriented Models for Identification and Representation of Lexical Collocations. Saarbrücken Dissertations in Computational Linguistics and Language Technology, Volume 7},
      YEAR = {2000},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Department of Computational Linguistics}
}

@PhdThesis{Krieger:1995,
      AUTHOR = {Krieger, Hans-Ulrich},
      TITLE = {TDL - A Type Description Language for Constraint-Based Grammars. Foundation, Implementation, and Application},
      YEAR = {1995},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Department of Computer Science},
      URL = {ftp://lt-ftp.dfki.uni-sb.de/pub/papers/local/diss.entry}
}

@PhdThesis{Kruijff-Korbayová:1998_1,
      AUTHOR = {Korbayova, Ivana},
      TITLE = {The Dynamic Potential of Topic and Focus: A Praguian Discourse Representation Theory},
      YEAR = {1998},
      ADDRESS = {Prague},
      SCHOOL = {Charles University, Faculty of Mathematics and Physics},
      NOTE = {unpublished}
}

@PhdThesis{Lehmann:2000,
      AUTHOR = {Lehmann, Sabine},
      TITLE = {Towards a Theory of Syntactic Phenomena. Saarbrücken Dissertations in Computational Linguistics and Language Technology, Volume 11},
      YEAR = {2000},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Fachbereich Computerlinguistik},
      URL = {http://www.dfki.de/~slehmann/thesis.pdf}
}

@PhdThesis{Mehl:1999,
      AUTHOR = {Mehl, Michael},
      TITLE = {The Oz Virtual Machine - Records, Transients, and Deep Guards},
      YEAR = {1999},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes},
      URL = {ftp://ftp.ps.uni-sb.de/pub/papers/ProgrammingSysLab/mehl-thesis.ps.gz},
      ABSTRACT = {In this thesis we describe the design and implementation of a virtual machine LVM for the execution of Oz programs. Oz is a concurrent, dynamically typed, functional language with logic variables, futures, by-need synchronization, records, feature constraints, and deep guard conditionals. The LVM supports light-weight threads, first-class procedures, exception handling, transients as generalization of logic variables, futures, and constraint variables, records and open records, and multiple computation spaces to implement the deep guard conditional. We discuss the modular, open, and extensible design of the LVM. Techniques for the efficient implementation of the store on standard hardware are shown. The LVM subsumes well-known virtual machines for functional, logic, and imperative languages.},
      ANNOTE = {COLIURL : Mehl:1999:OVM.pdf Mehl:1999:OVM.ps}
}

@PhdThesis{Müller:1998,
      AUTHOR = {Müller, Martin},
      TITLE = {Set-Based Failure Diagnosis for Concurrent Constraint Programming},
      YEAR = {1998},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Fachbereich Informatik},
      URL = {ftp://ftp.ps.uni-sb.de/pub/papers/ProgrammingSysLab/Diss-Mueller.ps.gz},
      ABSTRACT = {Oz is a recent high-level programming language, based on an extension of the concurrent constraint model by higher-order procedures and state. Oz is a dynamically typed language like Prolog, Scheme, or Smalltalk. We investigate two approaches of making static type analysis available for Oz: Set-based failure diagnosis and strong typing. We define a new system of set constraints over feature trees that is appropriate for the analysis of record structures, and we investigate its satisfiability, emptiness, and entailment problem. We present a set-based diagnosis for constraint logic programming and concurrent constraint programming as first-order fragments of Oz, and we prove that it correctly detects inevitable run-time errors. We also propose an analysis for a larger sublanguage of Oz. Complementarily, we define an Oz-style language called Plain that allows an expressive strong type system. We present such a type system and prove its soundness.},
      ANNOTE = {COLIURL : Muller:1998:SBF.pdf Muller:1998:SBF.ps}
}

@PhdThesis{Müller:1997_2,
      AUTHOR = {Müller, Stefan},
      TITLE = {Spezifikation und Verarbeitung deutscher Syntax in Head-Driven Phrase Structure Grammar},
      YEAR = {1997},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes}
}

@PhdThesis{Müller:2000_3,
      AUTHOR = {Müller, Stefan},
      TITLE = {Complex Predicates: Verbal Complexes, Resultative Constructions, and Particle Verbs in German},
      YEAR = {2000},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes},
      TYPE = {Habilitationsschrift},
      ABSTRACT = {In dem Buch entwickle ich eine Theorie der komplexen Prädikate, die normale Kopulakonstruktionen, kohärente Infinitive einschließich der AcI-Konstruktionen, Subjekt- und Objektprädikative, Resultativkonstruktionen und Partikelverben erfaßt. (1) Er fährt das Auto kaputt / zu Schrott. (2) Er ißt das Fleisch roh. Zur Abgrenzung der Resultativkonstruktionen (1) von anderen sekundäre Prädikaten wird auch auf depiktive Prädikate (2) eingegangen und eine entsprechende Analyse für diese entwickelt. Ich zeige, daß depiktive Prädikate als Adjunkte zu behandeln sind, die mit einem Element in der Argumentstruktur des Verbs, das sie modifizieren, koindiziert sind. Ich zeige auch, daß die Elemente in der Argumentstruktur des Verbs je nach ihrer Obliqueness als Antezedenten unterschiedlich gut geeignet sind. Im Teil, der sich mit Partikelverben beschäftigt, argumentiere ich, daß sich Verbzusätze wie andere Teile das Prädikatskomplexes verhalten. Sie werden wie Verben in der rechten Satzklammer angeordnet (3)-(4), können wie Adjektive oder Verben einzeln im Vorfeld stehen (5) oder bei Fokussierung wie Adjektive auch im Mittelfeld links vom Verbalkomplex angeordnet werden. (3) Karl kommt abends in Berlin an. (4) Karl kommt abends in der Stadt an, in der ich wohne. (5) Fest steht, daß Karl nicht der Mörder war. Es scheint also angebracht zu sein, die Verbzusatz-Verb-Konstruktionen syntaktisch wie Verbalkomplexe, also in der Syntax, zu behandeln. Wenn Verbzusätze analog zu anderen Elementen des Verbalkomplexes behandelt werden, kann (5) als Falle von (Partial) Verb Phrase Fronting behandelt werden. Für nicht-transparente Partikelverben nehme ich Lexikoneinträge an, die denen von verbalkomplexbildenden Verben ähneln. Lexikoneinträge, die in transparente Partikelverbkombinationen verwendet werden, werden durch Lexikonregeln lizensiert. Bei Behandlung der Partikeln als eigenständige syntaktische Einheiten stellt sich natürlich die Frage, wie die morphologischen Fakten, insbesondere die Derivation erklärt werden kann. In einer breiten empirischen Untersuchung werden Ähnlichkeiten zur Derivation mit Resultativkonstruktionen aufgezeigt und es wird deutlich gemacht, daß weder bei Resultativkonstruktionen noch bei Partikelverben Listedness für die Derivation entscheidend ist. Produktive Partikel-Verb-Verbindungen und die eindeutig syntaktischen Resultativkonstruktionen treten z.B. in ähnlicher Weise in vielen Nominalisierungsformen auf. Zur Beschreibung von Flexion und Derivation nehme ich Lexikonregeln an, die Stämme auf flektierte Formen bzw. Stämme auf andere Stämme abbilden. Im Fall der Partikelverben wird ein Stamm, der für eine Partikel subkategorisiert ist, durch Flexionsregeln auf ein Wort abgebildet, das dann in der Syntax mit der Partikel kombiniert werden kann. Alternativ kann der Stamm aber auch durch eine Derivationsregel auf einen anderen Stamm abgebildet werden, dieser Stamm muß dann natürlich auch flektiert werden. Da der Stamm für die Partikel subkategorisiert ist, haben Derivationsregeln Zugriff auf Information, die von der Partikel begesteuert wird (z.B. semantische Information bzw. Information über zusätzliche Komplemente zusätzliche Komplemente). Die vieldiskutierten Klammerparadoxa existieren für diesen Ansatz nicht. Mächtig Mittel wie Umklammerung (Rebrackating) werden nicht benötigt. Die Daten aus dem in diesem Buch enthaltenen Kapitel über Partikelverben wurden teilweise auf der HPSG 99 und dem Partikelverbworkshop in Leipzig präsentiert. Die Passivanalyse mit Lexikonregeln wurde auf der HPSG 2000 in Berkeley vorgestellt. Über komplexe Prädikate und Partikelverben habe ich auf der GGS 2000 in Potsdam vorgetragen. Über eine Lösung der Klammerparadoxa in der morphologischen Analyse der Partikelverben habe ich auf der HPSG 2001 in Trondheim gesprochen und die Analyse für depiktive Prädikate wurde auf der FG 2001 in Helsinki vorgestellt.}
}

@PhdThesis{Müller-Landmann:2000,
      AUTHOR = {Müller-Landmann, Sonja},
      TITLE = {Corpus-Based Parse Pruning - Applying Empirical Data to Symbolic Knowledge},
      YEAR = {2000},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Department of Computational Linguistics}
}

@PhdThesis{Netter:1996,
      AUTHOR = {Netter, Klaus},
      TITLE = {Functional Categories in an HPSG for German. Saarbrücken Dissertations in Computational Linguistics and Language Technology, Volume 3},
      YEAR = {1996},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Computational Linguistics}
}

@PhdThesis{Neumann:1994_1,
      AUTHOR = {Neumann, Günter},
      TITLE = {A Uniform Computational Model for Natural Language Parsing and Generation. Saarbruecken Dissertations in Computational Linguistics and Language Technology. Vol. 1},
      YEAR = {1994},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Computational Linguistics},
      URL = {http://www.dfki.de/~neumann/publications/new-ps/diss-gn.ps.gz},
      ANNOTE = {COLIURL : Neumann:1994:UCM.pdf Neumann:1994:UCM.ps}
}

@PhdThesis{Prescher:2002,
      AUTHOR = {Prescher, Detlef},
      TITLE = {EM-basierte maschinelle Lernverfahren für natürliche Sprachen},
      YEAR = {2002},
      NUMBER = {8(1)},
      SERIES = {AIMS Report},
      ADDRESS = {Stuttgart},
      SCHOOL = {Universität Stuttgart, Institut für Maschinelle Sprachverarbeitung (IMS)},
      URL = {http://www.dfki.de/~prescher/papers/bib/2002phd.prescher.pdf},
      ABSTRACT = {This thesis presents the Expectation-Maximization algorithm (EM algorithm, Dempster et al. (1977)) in its practical and theoretical aspects. The EM algorithm is the stochastic basis of many machine learning algorithms for natural language processing. In the theoretical part of this thesis the stochastic basis of linguistics and the formal basis of the EM algorithm is explained. The practical part of this thesis presents a probabilistic clustering method for multivariate linguistic data and stochastic modeling of lexicalized grammars.},
      ANNOTE = {COLIURL : Prescher:2002:EBM.pdf}
}

@PhdThesis{Pützer:1989,
      AUTHOR = {Pützer, Manfred},
      TITLE = {Die Mundart von Großrosseln},
      YEAR = {1989},
      ADDRESS = {Saarbrücken, Germany}
}

@PhdThesis{Pützer:2004,
      AUTHOR = {Pützer, Manfred},
      TITLE = {Stimmqualität und linguistische Funktionalität in der individuell referentiellen Bewertung. Ein instrumenteller und auditiver Beitrag zu Phonations- und Artikulationsvaria-tionen bei Dysarthrophonien},
      YEAR = {2004},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Department of Computational Linguistics},
      TYPE = {Habilitation Thesis}
}

@PhdThesis{Samuelsson:1994_2,
      AUTHOR = {Samuelsson, Christer},
      TITLE = {Fast Natural-Language Parsing Using Explanation-Based Learning},
      YEAR = {1994},
      ADDRESS = {Stockholm},
      SCHOOL = {The Royal Institute of Technology}
}

@PhdThesis{Scheidhauer:1998,
      AUTHOR = {Scheidhauer, Ralf},
      TITLE = {Design, Implementierung und Evaluierung einer virtuellen Maschine für Oz},
      YEAR = {1998},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Fachbereich Informatik},
      URL = {ftp://ftp.ps.uni-sb.de/pub/papers/ProgrammingSysLab/scheidhauer-thesis.ps.gz},
      ABSTRACT = {This thesis presents the design, implementation and evaluation of a virtual machine for the core language of Oz, which we call L. We present L for didactic reasons as an extension of a sublanguage of SML. The most important differences between L and SML are: logic variables, threads, synchronization and dynamic typing. Starting from an informal description of the dynamic semantics in terms of a graph model, we develop step by step on various levels of abstraction a virtual machine for L. We begin with a simple basic model. We then propose several optimizations of this model. Afterwards we keep refining our approach by addressing specific aspects of the implementation of the model. Finally we evaluate the effectiveness of the techniques using a set of larger real world applications. Further we show, that the implementation of the language is competitive with the fastest emulators for statically typed functional languages.},
      ANNOTE = {COLIURL : Scheidhauer:1998:DIE.pdf Scheidhauer:1998:DIE.ps}
}

@PhdThesis{Siegel:1996_3,
      AUTHOR = {Siegel, Melanie},
      TITLE = {Die maschinelle Übersetzung aufgabenorientierter japanisch-deutscher Dialoge. Lösungen für Translation Mismatches},
      YEAR = {1996},
      URL = {http://www.dfki.de/~siegel/diss.ps.gz},
      ANNOTE = {COLIURL : Siegel:1996:MUA.pdf Siegel:1996:MUA.ps}
}

@PhdThesis{Skut:1999,
      AUTHOR = {Skut, Wojciech},
      TITLE = {Partial Parsing for Corpus Annotation and Text Processing},
      YEAR = {1999},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes}
}

@PhdThesis{Vasishth:2002_2,
      AUTHOR = {Vasishth, Shravan},
      TITLE = {Working Memory in Sentence Comprehension: Processing Hindi Center Embeddings},
      YEAR = {2002},
      MONTH = {June},
      ADDRESS = {Columbus},
      SCHOOL = {Ohio State University, Department of Linguistics},
      URL = {http://www.ling.ohio-state.edu/~vasishth/PhD/diss.pdf.gz http://www.ling.ohio-state.edu/~vasishth/PhD/diss.ps.gz},
      NOTE = {To appear in the Garland series, Routledge Press, NY},
      ANNOTE = {COLIURL : Vasishth:2002:WMS.pdf}
}

@PhdThesis{Wirén:1992,
      AUTHOR = {Wirén, Mats},
      TITLE = {Studies in Incremental Natural-Language Analysis},
      YEAR = {1992},
      ADDRESS = {Linköping},
      SCHOOL = {Linköping University, Department of Computer and Information Science}
}

@PhdThesis{Würtz:1998,
      AUTHOR = {Würtz, Jörg},
      TITLE = {Lösen kombinatorischer Probleme mit Constraintprogrammierung in Oz},
      YEAR = {1998},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, FB Informatik},
      URL = {ftp://ftp.ps.uni-sb.de/pub/papers/ProgrammingSysLab/WuertzDiss-98.ps.gz},
      ABSTRACT = {In dieser Dissertation beschäftigen wir uns mit der Lösung kombinatorischer Probleme durch Constraintprogrammierung. Wir zeigen, dass verschiedene kombinatorische Probleme in der nebenläufigen Constraintsprache Oz effizient gelöst werden können. Wir führen ein formales Modell von constraintbasiertem Lösen kombinatorischer Probleme ein, das unabhängig von einer konkreten Programmiersprache ist, und wir zeigen, wie einige der derzeit besten Schedulingtechniken (Techniken für Ablaufplanung) aus dem Operations Research für Constraintpropagierung und Distribuierung in dieses Modell integriert werden können. Wir zeigen, wie dieses Modell in die nebenläufige Constraintsprache Oz eingebettet werden kann und belegen mit einer Reihe von Fallstudien für große und schwierige Probleme aus dem Gebiet des Scheduling die Leistungsfähigkeit des entwickelten Systems.},
      ANNOTE = {COLIURL : Wurtz:1998:LKP.ps}
}

@PhdThesis{Erk:2002,
      AUTHOR = {Erk, Katrin},
      TITLE = {Parallelism Constraints in Underspecified Semantics},
      YEAR = {2002},
      MONTH = {December},
      SCHOOL = {Saarland University},
      URL = {http://www.ps.uni-sb.de/Papers/abstracts/disserk.html}
}

@PhdThesis{Avgustinova:2002_2,
      AUTHOR = {Avgustinova, Tania},
      TITLE = {Shared Grammatical Resources for Slavic Languages. Selected topic in multilingual grammar design with special reference to Slavic morphosyntax},
      YEAR = {2002},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes},
      TYPE = {Habilitationsschrift}
}

@PhdThesis{Kordoni:2001_2,
      AUTHOR = {Kordoni, Valia},
      TITLE = {Psych Verb Constructions in Modern Greek: a semantic analysis in the Hierarchical Lexicon},
      YEAR = {2001},
      ADDRESS = {Colchester, UK},
      ORGANIZATION = {Kordoni:2001:PVC},
      SCHOOL = {University of Essex},
      URL = {https://www.coli.uni-saarland.de/~kordoni/thesis.html}
}

@PhdThesis{An2007,
      AUTHOR = {Andreeva, Bistra},
      TITLE = {Zur Phonetik und Phonologie der Intonation der Sofioter-Varietät des Bulgarischen, PHONUS 12},
      YEAR = {2007},
      SCHOOL = {Saarbrücken: Institute of Phonetics, University of the Saarland},
      NOTE = {WB}
}

@PhdThesis{Zh2007,
      AUTHOR = {Zhang, Yi},
      TITLE = {Robust deep linguistic processing},
      YEAR = {2007},
      SCHOOL = {Saarland University, Saarbrücken, Germany},
      NOTE = {HU}
}

@PhdThesis{Puet2007,
      AUTHOR = {Pützer, Manfred},
      TITLE = {Die Rolle kortikaler und subkortikaler Strukturen bei der Initiierung und Produktion artikulatorisch differenzierter CV-Silbenwiederholungen. Eine fMRT-Studie},
      YEAR = {2007},
      SCHOOL = {Medizinische Fakultät, Universität des Saarlandes},
      NOTE = {WB}
}

@PhdThesis{Fl2007,
      AUTHOR = {Fliedner, Gerhard},
      TITLE = {Linguistically Informed Question Answering},
      YEAR = {2007},
      ADDRESS = {Universität des Saarlandes, Saarbücken},
      SCHOOL = {Institut für Computerlinguistik, Saarbrücken Dissertations in Computational Linguistic and Language Technology, vol. XXIII},
      NOTE = {MP}
}

@PhdThesis{Pad2007,
      AUTHOR = {Pado, Ulrike},
      TITLE = {The Integration of Syntax and Semantic Plausibility in a Wide-Coverage Model of Human Sentence Processing},
      YEAR = {2007},
      SCHOOL = {Saarland University},
      NOTE = {MC}
}

@PhdThesis{SPa2007,
      AUTHOR = {Pado, Sebastian},
      TITLE = {Cross-Lingual Annotation Projection Models for Role-Semantic Information},
      YEAR = {2007},
      SCHOOL = {Saarland University},
      NOTE = {MP}
}

@PhdThesis{Xu2007,
      AUTHOR = {Xu, Feiyu},
      TITLE = {Feiyu Xu
Bootstrapping Relation Extraction from Semantic Seeds},
      YEAR = {2007},
      SCHOOL = {Saarland University},
      NOTE = {HU}
}

@PhdThesis{Am2009,
      AUTHOR = {Amoia, Marilisa},
      TITLE = {Linguistic-based computational treatment of textual entailment recognition},
      YEAR = {2009},
      SCHOOL = {Universität des Saarlandes, Fakultät 4 - Philosophische Fakultät II: Fachrichtung 4.7 - Allgemeine Linguistik, Lehrstuhl Prof. Dr. Manfred Pinkal: Professur für Computerlinguistik},
      NOTE = {MP}
}

@PhdThesis{Ri2008,
      AUTHOR = {Rieser, Verena},
      TITLE = {Bootstrapping reinforcement learning-based dialogue strategies from Wizard-of-Oz data},
      YEAR = {2008},
      VOLUME = {28},
      SERIES = {Saarbrücken dissertations in computational linguistics and language technology},
      ORGANIZATION = {German Research Center for Artifical Intelligence [u.a.]},
      SCHOOL = {Universität des Saarlandes, Fakultät 4 - Philosophische Fakultät II: Fachrichtung 4.7 - Allgemeine Linguistik, Lehrstuhl Prof. Dr. Manfred Pinkal: Professur für Computerlinguistik},
      NOTE = {MP}
}

@PhdThesis{Sh2008,
      AUTHOR = {Shen, Dan},
      TITLE = {Exploring rich evidence for maximum entropy-based question answering},
      YEAR = {2008},
      SCHOOL = {Universität des Saarlandes},
      NOTE = {DK}
}

@PhdThesis{Me2008,
      AUTHOR = {Merkel, Andreas},
      TITLE = {Using language models in question answering},
      YEAR = {2008},
      SCHOOL = {Universität des Saarlandes},
      NOTE = {DK}
}

@PhdThesis{Bu2008,
      AUTHOR = {Burchardt, Aljoscha},
      TITLE = {Modeling textual entailment with role-semantic information},
      YEAR = {2008},
      VOLUME = {29},
      SERIES = {Saarbrücken dissertations in computational linguistics and language technology},
      ORGANIZATION = {German Research Center for Artifical Intelligence [u.a.]},
      SCHOOL = {Universität des Saarlandes, Fakultät 4 - Philosophische Fakultät II: Fachrichtung 4.7 - Allgemeine Linguistik, Lehrstuhl Prof. Dr. Manfred Pinkal: Professur für Computerlinguistik},
      NOTE = {MP}
}

@PhdThesis{Dr2009,
      AUTHOR = {Dridan, Rebecca},
      TITLE = {Using lexical statistics to improve HPSG parsing},
      YEAR = {2009},
      SCHOOL = {Universität des Saarlandes},
      NOTE = {HU}
}

@PhdThesis{IS2010a,
      AUTHOR = {Steiner, Ingmar},
      TITLE = {Observations on the dynamic control of an articulatory synthesizer using speech production data},
      YEAR = {2010},
      SCHOOL = {Universität des Saarlandes},
      NOTE = {WB}
}

@PhdThesis{Wi2011,
      AUTHOR = {Wiegand, Michael},
      TITLE = {Hybrid approaches for sentiment analysis},
      YEAR = {2011},
      SCHOOL = {Universität des Saarlandes},
      ABSTRACT = {Sentiment Analysis is the task of extracting and classifying opinionated content in natural language texts. Common subtasks are the distinction between opinionated and factual texts, the classification of polarity in opinionated texts, and the extraction of the participating entities of an opinion(-event), i.e. the source from which an opinion emanates and the target towards which it is directed. With the emerging Web 2.0 which describes the shift towards a highly user-interactive communication medium, the amount of subjective content on the World Wide Web is steadily increasing. Thus, there is a growing need for automatically processing this type of content which is provided by sentiment analysis. Both natural language processing, which is the task of providing computational methods for the analysis and representation of natural language, and machine learning, which is the task of building task-specific classification models on the basis of empirical data, may be instrumental in mastering the challenges of the automatic sentiment analysis of written text. Many problems in sentiment analysis have been proposed to be solved with machine learning methods exclusively using a fairly low-level feature design, such as bag of words, containing little linguistic information. In this thesis, we examine the effectiveness of linguistic features in various subtasks of sentiment analysis. Thus, we heavily draw from the insights gained by natural language processing. The application of linguistic features can be applied on various classification methods, be it in rule-based classification, where the linguistic features are directly encoded as a classifier, in supervised machine learning, where these features complement basic low-level features, or in bootstrapping methods, where these features form a rule-based classifier generating a labeled training set from which a supervised classifier can be trained. In this thesis, we will in particular focus on scenarios where the combination of linguistic features and machine learning methods is effective. We will look at common text classification tasks, both coarse-grained and fine-grained, and extraction tasks.},
      NOTE = {DK}
}

@PhdThesis{Cra2011,
      AUTHOR = {Cramer, Bart},
      TITLE = {Improving the feasibility of precision-oriented HPSG parsing},
      YEAR = {2011},
      SCHOOL = {Universität des Saarlandes}
}

@PhdThesis{Pam2011,
      AUTHOR = {Pammi, Sathish Chandra},
      TITLE = {Synthesis of listener vocalizations : towards interactive speech synthesis},
      YEAR = {2011},
      SCHOOL = {Universität des Saarlandes},
      NOTE = {Volltext zu diesem Titel erhältlich in SciDok: urn:nbn:de:bsz:291-scidok-45727}
}

@PhdThesis{Sac2012,
      AUTHOR = {Sacaleanu, Bogdan},
      TITLE = {Synthesis of listener vocalizations : towards interactive speech synthesis},
      YEAR = {2012},
      SCHOOL = {Universität des Saarlandes},
      NOTE = {Volltext zu diesem Titel erhältlich in SciDok:
urn:nbn:de:bsz:291-scidok-47820}
}

@PhdThesis{Schr2011,
      AUTHOR = {Schröder, Marc},
      TITLE = {The SEMAINE API : a component integration framework for a naturally interacting and emotionally competent embodied conversational agent},
      YEAR = {2011},
      SCHOOL = {Universität des Saarlandes},
      NOTE = {Volltext zu diesem Titel erhältlich in SciDok:
urn:nbn:de:bsz:291-scidok-45446}
}

@PhdThesis{Ve2012,
      AUTHOR = {Vela, Mihaela},
      TITLE = {Extraction of ontology schema components from financial news},
      YEAR = {2012},
      SCHOOL = {Universität des Saarlandes},
      NOTE = {Volltext zu diesem Titel erhältlich in SciDok:
urn:nbn:de:bsz:291-scidok-47060}
}

@PhdThesis{Wa2011,
      AUTHOR = {Wang, Rui},
      TITLE = {Wang, Rui

Intrinsic and extrinsic approaches to recognizing textual entailment},
      YEAR = {2011},
      SCHOOL = {Universität des Saarlandes}
}

@PhdThesis{Kö2011,
      AUTHOR = {Köhne, Judith},
      TITLE = {The interactive nature of second-language word learning in non-instructed environments},
      YEAR = {2011},
      SCHOOL = {Universität des Saarlandes},
      NOTE = {Volltext zu diesem Titel erhältlich in SciDok:
urn:nbn:de:bsz:291-scidok-45152}
}

@PhdThesis{Li2012,
      AUTHOR = {Li, Linlin},
      TITLE = {Computational modeling of lexical ambiguity},
      YEAR = {2012},
      SCHOOL = {Universität des Saarlandes},
      NOTE = {sonst. Mitarbeiter}
}

@PhdThesis{Sun2012,
      AUTHOR = {Sun, Weiwei},
      TITLE = {Learning Chinese language structures with multiple views},
      YEAR = {2012},
      SCHOOL = {Universität des Saarlandes},
      NOTE = {HU}
}

@PhdThesis{Reg2013,
      AUTHOR = {Regneri, Michaela},
      TITLE = {Event structures in knowledge, pictures and text},
      YEAR = {2014},
      SCHOOL = {Universität des Saarlandes},
      NOTE = {MP}
}

@PhdThesis{Fed2013b,
      AUTHOR = {Federmann, Christian},
      TITLE = {Hybrid machine translation using binary classification models trained on joint, binarised feature vectors},
      YEAR = {2013},
      SCHOOL = {Universität des Saarlandes},
      ABSTRACT = {We describe the design and implementation of a system combination method for machine translation output. It is based on sentence selection using binary classification models estimated on joint, binarised feature vectors. By contrast to existing system combination methods which work by dividing candidate translations into n-grams, i.e., sequences of n words or tokens, our framework performs sentence selection which does not alter the selected, best translation. First, we investigate the potential performance gain attainable by optimal sentence selection. To do so, we conduct the largest meta-study on data released by the yearly Workshop on Statistical Machine Translation (WMT). Second, we introduce so-called joint, binarised feature vectors which explicitly model feature value comparison for two systems A, B. We compare different settings for training binary classifiers using single, joint, as well as joint, binarised feature vectors. After having shown the potential of both selection and binarisation as methodological paradigms, we combine these two into a combination framework which applies pairwise comparison of all candidate systems to determine the best translation for each individual sentence. Our system is able to outperform other state-of-the-art system combination approaches; this is confirmed by our experiments. We conclude by summarising the main findings and contributions of our thesis and by giving an outlook to future research directions.},
      NOTE = {HU}
}

@PhdThesis{Arn2013,
      AUTHOR = {Arnold, Denis},
      TITLE = {Die Erhebung perzeptueller Prominenz auf Silben- und Wortebene : der Einfluss von Bewertungsskalen, Bewertungsebenen und Normalisierung},
      YEAR = {2013},
      SCHOOL = {Universität des Saarlandes},
      ABSTRACT = {Die vorliegende Dissertation beschäftigt sich mit verschieden Methoden zur Erhebung von perzeptuellen Prominenzurteilen von naiven Hörern im Deutschen. Es werden zwei Experimente vorgestellt, die sich zum einen mit der Verwendung von verschiedenen Skalen, zum anderen mit der Verwendung von unterschiedlichen Bewertungsebenen zur Beurteilung von perzeptueller Prominenz beschäftigen. Die Ergebnisse zeigen, dass Ergebnisse von Studien, welche auf unterschiedlichen Erhebungstechniken beruhen nicht ohne weiteres vergleichbar sind. Die Arbeit untersucht außerdem die Effekte einer Normalisierung der Prominenzurteile. Die Dissertation schließt mit einem Ausblick für zukünftige Studien. Hierbei werden hauptsächlich die vielfältigen Interaktionen von verschiedenen Quellen und dem Kontext bei der Beurteilung der perzeptuellen Prominenz adressiert.},
      NOTE = {BM}
}

@PhdThesis{Las2014,
      AUTHOR = {Lasarcyk, Eva},
      TITLE = {Empirical evaluation of the articulatory synthesizer VocalTractLab as a discovery tool for phonetic research: Articulatory-acoustic investigations of paralinguistic speech phenomena.},
      YEAR = {2014},
      ADDRESS = {Saarbrücken: Institute of Phonetics},
      SCHOOL = {Saarland University},
      NOTE = {MB}
}