Computer Science
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Ehfayed, Shneina (, 2013)[more][less]
Zusammenfassung: This thesis has been written under the supervision of my mentor Prof. Dr. Pavle Mladenović at the University of Belgrade, Faculty of Mathematics in the academic year 2012-2013. The title of this thesis is “Extreme values in sequences of independent random variables with mixed distributions”. For good survey of the field, see Resnick, S. I. [25] and Samorodnitsky, Taqqu [27]. The thesis is divided into two chapters. Chapter 1 is divided into 7 sections. In this chapter, we focus on classical results in extreme value theory. We discuss maxima and minima in the first section, univariate extreme value theory in the second section, max-stable distributions in the third section, peaks over threshold models in the fourth section, domain of attraction of the extremal type distributions in the fifth section, tails in the sixth section and tail equivalence in the seventh section. Chapter 2 is divided into 9 sections. In this chapter, we discuss mixed distributions in the first section, mixture of normal distributions in the second section, mixture of Cauchy distributions in the third section, stable distributions in the fourth section, properties of stable random variables in the fifth section, infinitely divisible distributions in the sixth section. Sections 7 and 8 contain the main results for this dissertation. Mixtures of stable distributions are described in the seventh section and mixtures of an infinite sequence of independent normally distributed variables in the eighth section. Conclusion and future research are in the ninth section. URI: http://hdl.handle.net/123456789/5838 Dateien zu dieser Ressource: 1
Disertacija4277.pdf ( 2.285Mb ) -
Vujičić Stanković, Staša (Beograd , 2016)[more][less]
Zusammenfassung: The basic goal of this doctoral thesis is a research into different techniques and models which are applied in information extraction, and providing an informatic support in processing of natural language texts from culinary and gastronomy domain. Information extraction is a subfield of computational linguistics which includes techniques for natural languages processing, in order to find relevant information, define their meaning and establish relations between them. A very special attention is given to ontology based information extraction. It consists of the following: recognition of instances of ontology concepts in non‐structured or semi‐ structured texts written in natural language, reasoning over the identified instances based on the rules defined in the ontology, as well as recognition of instances and their use for instantiating the proper ontology concepts. The main result of thesis reflects in the presentation of a new model for ontology based information extraction. Besides solving tasks of information extraction, the new model includes not only upgrade of existing lexical resources and ontologies, but also creation of the new ones. Its application resulted in development of a system for extraction of information related to the culinary domain, but this new model can be used in other fields as well. Beside this, the food ontology has been developed, Serbian WordNet is extended for another 1.404 synsets from the culinary domain, while electronic dictionary of Serbian is enlarged with 1.248 entries. The significance of the model application comes from the fact that the new and enriched linguistic resources can be used in other systems for natural language processing. The opening chapter of the thesis elaborates the need of providing an informatic model for processing a huge linguistic corpus related to culinary and gastronomy domain, through methodologically precise and solid approach integrating pieces of information on the domain. Also, the formalization of the basic research subject, text in electronic form, has been presented. Further on, the chapter contains a description of the natural languages approximations introduced in order to enable modern information technologies to process texts written in natural languages, and it emphasizes the need to make the characterisation of the text language with corresponding corpus and sublanguage. Further on in the first chapter, the task of information extraction, and the models for informatic processing of non‐structured or semi‐structured texts, used by the computer to interpret the meaning that the author (not necessarily a human) has intended to give while writing the text, are defined. Additionally, this chapter contains the description of the methods used in information extraction field – methods based on rules and methods based on machine learning. Their advantages and shortcomings are listed, so as the reasons why in this thesis are used techniques based on linguistic knowledge. As a conclusion to the introduction chapter, a special attention is given to ontologies, WordNet, and the significance of its usage as ontology. The second chapter contains the presentation of the linguistic resources and tools exploited in this thesis. It describes morphological dictionaries and local grammars used for solving the problem of information extraction from texts written in Serbian. A review of information extraction systems is given subsequently. At the end of the second chapter, the stages in processing of Serbian written texts during the information extraction in the software systems Unitex and GATE are described. The main result of the thesis is presented in the third chapter. It is the model for solving the problem of information extraction by integrating linguistic resources and tools, which includes creation of a text corpus, definition of tasks for information extraction, establishment of finite state models for information extraction, and their application accordingly, iterative enlarging of electronic morphological dictionaries, enrichment and enhancement of WordNet, and creation of new ontologies. Each of these steps is described thoroughly. Even though the model was at first considered as a solution for problems in processing Serbian, it can be equally applied for processing texts written in other languages, with the development of suitable language resources accordingly. The implementation of the above explained steps is described in the fourth chapter, through a system for information extraction from the culinary texts written in Serbian. Then follows the description of a bond in the development and mutual complement of lexical resources through steps in creating domain corpus, identifying culinary lexica, expanding and upgrading of WordNet and electronic morphological dictionaries, and developing of domain ontologies – the food ontology, the approximate measure ontology, and the ontology of ingredients that can be used as mutual replacements in the culinary domain. This system, developed for information extraction, has served for creating an advanced search system which, based on a corpus of culinary texts, generates all possible answers to inquiries made by users. In the frame of this system is implemented a specific method which serves for creation of links between different recipes. This is used in case when the user reviews a text of a recipe and notices that in preparing description features some part which already had appeared in other recipe, but with additional or different explanation. Another contribution of this thesis is application of developed ontologies in tasks that convert approximate measures into standard measures, and establishment of similarities among the recipes. The similarity of the recipes is defined as similarity of texts which describe process of course preparation in accordance with a specific recipe. The last chapter contains final conclusions and directions for future research. URI: http://hdl.handle.net/123456789/5836 Dateien zu dieser Ressource: 1
Disertacija_10_21.pdf ( 10.38Mb ) -
Banković, Milan (Beograd , 2016)[more][less]
Zusammenfassung: SMT solvers implement decision procedures that check for satisfiability of first-order logical formulae with respect to some decidable theory. They rely on the powerful techniques that are used for solving boolean satisfiability problem (SAT), combined with specific procedures that permit reasoning in a particular theory. Typical applications of SMT solvers are mostly found in software verification, and for this reason the theories frequently considered in SMT solvers are best suited for such kind of applications. Extending the applicability of SMT solvers to other areas may require defining new SMT theories, as well as developing the corresponding decision procedures for such theories. In that sense, in this thesis we consider improving of SMT solvers by extending their applicability to solving CSP problems. Such problems consider variables with finite domains, and the goal is to find the assignment of values to the variables of the problem satisfying all the imposed constraints. When CSP solving is considered, the main drawback of the existing SMT theories is that they are not adapted to the problems with finite domains, and are also incapable of reasoning about global constraints, which play the significant role in most CSP problems. For this reason, in this thesis a novel SMT theory is defined that enables natural representation of CSP problems, since it includes support for some frequently used global constraints. For such theory, we developed a decision procedure based on the existing techniques borrowed from the traditional CSP solvers, but these techniques are adapted in the way that permits their usage within SMT solvers. The decision procedure currently supports two types of global constraints: the alldifferent constraint and the linear constraint. In case of the alldifferent constraint, the main contribution is a novel algorithm for generating explanations of conflicts and propagations, which is required for the conflict analysis. In case of the linear constraint, a novel filtering algorithm is developed that takes into consideration the existence of the alldifferent constraints in the given problem, which can lead to a stronger propagation. Another direction of improving SMT solvers that is considered in the thesis is the usage of the parallelization techniques. We consider the parallelization of the simplex algorithm, which is used in SMT solvers as the decision procedure for the linear arithmetic. We also consider the parallel portfolio approach, as well as the hybridization of the two approaches. A comprehensive experimental evaluation is provided on a large number of instances, both industrial and randomly generated. For the purpose of all the mentioned research, during the work on the thesis a new open-source SMT solver called argosmt is developed, based on DPLL(T ) architecture. URI: http://hdl.handle.net/123456789/5835 Dateien zu dieser Ressource: 1
Disertacija_8.pdf ( 2.359Mb ) -
Šandrih, Branislava (Beograd , 2020)[more][less]
Zusammenfassung: The main goal of this dissertation is to put different text classification tasks in the same frame, by mapping the input data into the common vector space of linguistic attributes. Subsequently, several classification problems of great importance for natural language processing are solved by applying the appropriate classification algorithms. The dissertation deals with the problem of validation of bilingual translation pairs, so that the final goal is to construct a classifier which provides a substitute for human evalu- ation and which decides whether the pair is a proper translation between the appropriate languages by means of applying a variety of linguistic information and methods. In dictionaries it is useful to have a sentence that demonstrates use for a particular dictio- nary entry. This task is called the classification of good dictionary examples. In this thesis, a method is developed which automatically estimates whether an example is good or bad for a specific dictionary entry. Two cases of short message classification are also discussed in this dissertation. In the first case, classes are the authors of the messages, and the task is to assign each message to its author from that fixed set. This task is called authorship identification. The other observed classification of short messages is called opinion mining, or sentiment analysis. Starting from the assumption that a short message carries a positive or negative attitude about a thing, or is purely informative, classes can be: positive, negative and neutral. These tasks are of great importance in the field of natural language processing and the proposed solutions are language-independent, based on machine learning methods: sup- port vector machines, decision trees and gradient boosting. For all of these tasks, a demonstration of the effectiveness of the proposed methods is shown on for the Serbian language. URI: http://hdl.handle.net/123456789/5801 Dateien zu dieser Ressource: 1
Disertacija.pdf ( 9.053Mb ) -
Veljković, Aleksandar (Beograd , 2023)[more][less]
Zusammenfassung: Bioinformatics as a science of the future faces the problems of processing a large amount of data that is increasing every day. In addition to the problem of data storage, the challenge is also data analysis and the understanding of hidden relations between biological entities that are observed only after unifying data from different data sources. This thesis proposes a novel data model for the unification of heterogeneous data from multiple bioinformatics databases and a system architecture design for implementing software systems based on the proposed data model. Additionally, the thesis defines an automated pipeline for discovering new semantic similarity relations based on data mining methods using the data found in the proposed data model. The data model, software architecture, and automatic pipeline are evaluated using data from five real-world bioinformatics databases. The results demonstrate a high flexibility of the data model and the high efficiency of the software system implemented following the proposed architecture design. URI: http://hdl.handle.net/123456789/5794 Dateien zu dieser Ressource: 1
Disertacija_15649.pdf ( 2.864Mb )