CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / Esse trabalho possui um recorte teÃrico-metodolÃgico que se decompÃe em dois domÃnios complementares: o LinguÃstico e o Computacional/Implementacional. Pelo seu cunho computacional, o escopo primeiro desse trabalho està diretamente ligado ao processamento de lÃngua natural (PLN). Desse modo, implementa-se uma anÃlise sintÃtica automÃtica (parsing) de expressÃes de lÃngua portuguesa em programas da biblioteca em Python do NLTK, cujas anÃlises sÃo representadas em forma de configuraÃÃes arbÃreas que demonstram categorias vazias de sentenÃas finitas do portuguÃs. Ainda pelo cunho computacional, esse trabalho elabora um fragmento de gramÃtica, modelado para capturar traÃos especÃficos da estrutura linguÃstica do portuguÃs, com base no modelo formal de descriÃÃo linguÃstica conhecido como GramÃtica Livre de Contexto (CFG) Baseada em TraÃos, com a finalidade de demonstrar como a biblioteca de programas do NLTK dà suporte à realizaÃÃo dos analisadores sintÃticos na anÃlise da estrutura de traÃos. Pelo seu cunho lingÃÃstico, analisa-se, de acordo com a Teoria X-barra e o Programa Minimalista, frases nas variantes europeia e brasileira da lÃngua portuguesa, obtidas de pesquisas em corpora eletrÃnicos disponÃveis na web. E ainda nesse trabalho, descreve-se e discute-se a categoria IP (sintagma flexional) dentro da sua estrutura hierÃrquica de constituintes, de acordo com a hipÃtese da operaÃÃo sintÃtica de movimento visÃvel e nÃo visÃvel dos elementos linguÃsticos, especificamente o movimento do verbo / This work has a theoretical and methodological framework that is divided into two complementary areas: the Language and Computational/Implementacional. For its computational stamp, the first scope of this work is directly linked to the processing of natural language (PNL). Thus, it implements an automatic syntactic analysis (parsing) of expressions of Portuguese in a computational program from the Python library of NLTK, whose tests are represented in tree configurations that show slash categories of finite sentences of Portuguese. Although the stamp computing, this research elaborates a grammar fragment, modeled to capture specific features of linguistic structure of Portuguese, based on the formal model of description linguistic known as Context Free Grammar (CFG) Based on Features, with the purpose of demonstrate how the library of NLTK programs supports the implementation of parsers for analyzing the feature structure. For its stamp of language, it analyzes, according to X-bar Theory and the Minimalist Program, sentences in European and Brazilian variants of Portuguese, obtained from surveys in electronic corpora available on the web. And this work describes and discusses the category IP (inflectional phrase) within the hierarchical structure of constituents, according to the hypothesis of syntactic operation of visible and invisible movement of elements of language, specifically the movement of the verb

p, li { white-space: pre-wrap; } The main goal of this work is to analyze the creation of the composite compiler. Composite compiler is in this case a szstem, which consists of more cooperating parts. My compiler is special, because its syntactic analyser consists of two parts. The work is focused on the construction of the parsers parts, on its cooperation and comunication. I will trys to scatch the teoretical backgroun of this solution. This is to be done by gramatical systems. Then I~will try to justify whether or not it is neccesary and suitable to create such a kind of parser. Last but not least I~will analyse the language, whose syntactic analyser is to be implemented by the chosen method.

<p>In the last decade, web browsers have seen a remarkable increase of performance, especially in the JavaScript engines. JavaScript has over the years gone from being a slow and rather limited language, to today have become feature-rich and fast. It’s speed can be around the same or half of comparable code written in C++, but this speed is directly dependent on the choice of the web browser, and the best performance is seen in browsers using JIT compilation techniques.</p><p>Even though the language has seen a dramatic increase in performance, there’s still major problems regarding memory usage. JavaScript applications typically consume 3-4 times more memory than similar applications written in C++. Many browser vendors, like Opera Software, acknowledge this and are currently trying to optimize their memory usage. This issue is hopefully non-existent within a near future.</p><p>Because the majority of scientific papers written about JavaScript only compare performance using the industry benchmarks SunSpider and V8, this thesis have chosen to widen the scope. The benchmarks really give no information about how JavaScript stands in comparison to C#, C++ and other popular languages. To be able to compare that, I’ve implemented a GIF decoder, an XML parser and various elementary tests in both JavaScript and C++ to compare how far apart the languages are in terms of speed, memory usage and responsiveness.</p>

Submitted by Ronildo Prado (ronisp@ufscar.br) on 2017-08-23T18:26:08Z No. of bitstreams: 1 DissPBC.pdf: 1229668 bytes, checksum: 806b06dd0fbdd6a4076384a7d0f90456 (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-08-23T18:26:15Z (GMT) No. of bitstreams: 1 DissPBC.pdf: 1229668 bytes, checksum: 806b06dd0fbdd6a4076384a7d0f90456 (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-08-23T18:26:21Z (GMT) No. of bitstreams: 1 DissPBC.pdf: 1229668 bytes, checksum: 806b06dd0fbdd6a4076384a7d0f90456 (MD5) / Made available in DSpace on 2017-08-23T18:26:28Z (GMT). No. of bitstreams: 1 DissPBC.pdf: 1229668 bytes, checksum: 806b06dd0fbdd6a4076384a7d0f90456 (MD5) Previous issue date: 2017-01-24 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / A dependency parser consists in inducing a model that is capable of extracting the right dependency tree from an input natural language sentence. Nowadays, the multilingual techniques are being used more and more in Natural Language Processing (NLP) (BROWN et al., 1995; COHEN; DAS; SMITH, 2011), especially in the dependency parsing task. Intuitively, a multilingual parser can be seen as vector of different parsers, in which each one is individually trained on one language. However, this approach can be a really pain in the neck in terms of processing time and resources. As an alternative, many parsing techniques have been developed in order to solve this problem (MCDONALD; PETROV; HALL, 2011; TACKSTROM; MCDONALD; USZKOREIT, 2012; TITOV; HENDERSON, 2007) but all of them depends on word alignment (TACKSTROM; MCDONALD; USZKOREIT, 2012) or word clustering, which increases the complexity since it is difficult to induce alignments between words and syntactic resources (TSARFATY et al., 2013; BOHNET et al., 2013a). A simple solution proposed recently (NIVRE et al., 2016a) uses an universal annotated corpus in order to reduce the complexity associated with the construction of a multilingual parser. In this context, this work presents an universal model for dependency parsing: the NNParser. Our model is a modification of Chen e Manning (2014) with a more greedy and accurate model to capture distributional representations (MIKOLOV et al., 2011). The NNparser reached 93.08% UAS in English Penn Treebank (WSJ) and better results than the state of the art Stack LSTM parser for Portuguese (87.93% × 86.2% LAS) and Spanish (86.95% × 85.7% LAS) on the universal dependencies corpus. / Um analisador sintático de dependência consiste em um modelo capaz de extrair a estrutura de dependência de uma sentença em língua natural. No Processamento de Linguagem Natural (PLN), os métodos multilíngues tem sido cada vez mais utilizados (BROWN et al., 1995; COHEN; DAS; SMITH, 2011), inclusive na tarefa de análise de dependência. Intuitivamente, um analisador sintático multilíngue pode ser visto como um vetor de analisadores sintáticos treinados individualmente em cada língua. Contudo, a tarefa realizada com base neste vetor torna-se inviável devido a sua alta demanda por recursos. Como alternativa, diversos métodos de análise sintática foram propostos (MCDONALD; PETROV; HALL, 2011; TACKSTROM; MCDONALD; USZKOREIT, 2012; TITOV; HENDERSON, 2007), mas todos dependentes de alinhamento entre palavras (TACKSTROM; MCDONALD; USZKOREIT, 2012) ou de técnicas de agrupamento, o que também aumenta a complexidade associada ao modelo (TSARFATY et al., 2013; BOHNET et al., 2013a). Uma solução simples surgiu recentemente com a construção de recursos universais (NIVRE et al., 2016a). Estes recursos universais têm o potencial de diminuir a complexidade associada à construção de um modelo multilíngue, uma vez que não é necessário um mapeamento entre as diferentes notações das línguas. Nesta linha, este trabalho apresenta um modelo para análise sintática universal de dependência: o NNParser. O modelo em questão é uma modificação da proposta de Chen e Manning (2014) com um modelo mais guloso e preciso na captura de representações distribuídas (MIKOLOV et al., 2011). Nos experimentos aqui apresentados o NNParser atingiu 93, 08% de UAS para o inglês no córpus Penn Treebank e resultados melhores do que o estado da arte, o Stack LSTM, para o português (87,93% × 86,2% LAS) e o espanhol (86,95% × 85,7% LAS) no córpus UD 1.2.

In the last decade, web browsers have seen a remarkable increase of performance, especially in the JavaScript engines. JavaScript has over the years gone from being a slow and rather limited language, to today have become feature-rich and fast. It’s speed can be around the same or half of comparable code written in C++, but this speed is directly dependent on the choice of the web browser, and the best performance is seen in browsers using JIT compilation techniques. Even though the language has seen a dramatic increase in performance, there’s still major problems regarding memory usage. JavaScript applications typically consume 3-4 times more memory than similar applications written in C++. Many browser vendors, like Opera Software, acknowledge this and are currently trying to optimize their memory usage. This issue is hopefully non-existent within a near future. Because the majority of scientific papers written about JavaScript only compare performance using the industry benchmarks SunSpider and V8, this thesis have chosen to widen the scope. The benchmarks really give no information about how JavaScript stands in comparison to C#, C++ and other popular languages. To be able to compare that, I’ve implemented a GIF decoder, an XML parser and various elementary tests in both JavaScript and C++ to compare how far apart the languages are in terms of speed, memory usage and responsiveness.

XML has emerged as leading document format for exchanging data. Because of vast amounts of XML documents available and transfered, there is a strong need to store and query information in these documents. However, the most companies are still using a RDBMS for their data warehouses and it is often necessary to combine legacy data with the ones in XML format, so it might be useful to consider storage possibilities for XML documents in a relation database. In this thesis we focused on structured and semi-structured data-based XML documents, because they are the most common when exchanging data and they can be easily validated against an XML schema. We propose a slightly modified Hybrid algorithm to shred doc- uments into relations using an XSD scheme and we allowed redundancy to make queries faster. Our goal was not to provide an academic solution, but fully working system supporting latest standards, which will beat up native XML databases both by performance and vertical scalability.

Master&#8217;s thesis describes theoretical basics, solution design, and implementation of constituency (phrasal) parser for Czech language, which is based on a part of speech association into phrases. Created program works with manually built and annotated Czech sample corpus to generate probabilistic context free grammar within runtime machine learning. Parser implementation, based on extended CKY algorithm, then for the input Czech sentence decides if the sentence can be generated by the created grammar and for the positive cases constructs the most probable derivation tree. This result is then compared with the expected parse to evaluate constituency parser success rate.

This master's thesis deals with data mining techniques and classification of the data into specified categories. The goal of this thesis is to implement a web portal for administration and classification of data from distributed sources. To achieve the goal, it is necessary to test different methods and find the most appropriate one for web articles classification. From the results obtained, there will be developed an automated application for downloading and classification of data from different sources, which would ultimately be able to substitute a user, who would process all the tasks manually.

Wie lassen sich Corporate Design-konforme Drucksachen erzeugen, ohne Zugang zur Gestaltung zu haben. Der Vortrag stellt das strukturierte Datenformat XML, die Transformationssprache XSLT, die Formatierungssprache XSL-FO und den FO-Prozessor Apache FOP vor. Am praktischen Beispiel des TU Chemnitz-Plakatgenerators wird erläutert, wie der Formatierungsprozess abläuft. Des Weiteren wird die Softwarearchitektur des Generators vorgestellt, der sich vorliegender XML-Schablonen bedient, um automatisch und dynamisch das Nutzer-Eingabeformular im Webbrowser zu erzeugen.

The goal of this dissertation is to implement an application for ASP to ASPX conversion. The ASP pages should be written in the VBScript language, the target language for ASPX will be C#. The application is developed on the .NET platform. The conversion process should be automatic. There should be no need to alter the converted files by a programmer. The first part of this dissertation introduces the whole problematic. It shows also current solutions. The next part is the analysis and the design of the application itself. The main part of this dissertation is the VBScript grammar conversion, problems while conversion and its solving.