A photograph typically depicts an aspect of the real world, such as an outdoor landscape, a portrait, or an event. The task of creating abstract digital representations of images has received a great deal of attention in the computer vision literature because it is rarely useful to work directly with the raw pixel data. The challenge of working with raw pixel data is that small changes in lighting can result in different digital images, which is not typically useful for downstream tasks such as object detection. One approach to representing an image is automatically extracting and quantising visual features to create a bag-of-terms vector. The bag-of-terms vector helps overcome the problems with raw pixel data but this unstructured representation discards potentially useful information about the spatial and semantic relationships between the parts of the image. The central argument of this thesis is that capturing and encoding the relationships between parts of an image will improve the performance of extrinsic tasks, such as image description or search. We explore this claim in the restricted domain of images representing events, such as riding a bicycle or using a computer. The first major contribution of this thesis is the Visual Dependency Representation: a novel structured representation that captures the prominent region–region relationships in an image. The key idea is that images depicting the same events are likely to have similar spatial relationships between the regions contributing to the event. This representation is inspired by dependency syntax for natural language, which directly captures the relationships between the words in a sentence. We also contribute a data set of images annotated with multiple human-written descriptions, labelled image regions, and gold-standard Visual Dependency Representations, and explain how the gold-standard representations can be constructed by trained human annotators. The second major contribution of this thesis is an approach to automatically predicting Visual Dependency Representations using a graph-based statistical dependency parser. A dependency parser is typically used in Natural Language Processing to automatically predict the dependency structure of a sentence. In this thesis we use a dependency parser to predict the Visual Dependency Representation of an image because we are working with a discrete image representation – that of image regions. Our approach can exploit features from the region annotations and the description to predict the relationships between objects in an image. In a series of experiments using gold-standard region annotations, we report significant improvements in labelled and unlabelled directed attachment accuracy over a baseline that assumes there are no relationships between objects in an image. Finally, we find significant improvements in two extrinsic tasks when we represent images as Visual Dependency Representations predicted from gold-standard region annotations. In an image description task, we show significant improvements in automatic evaluation measures and human judgements compared to state-of-the-art models that use either external text corpora or region proximity to guide the generation process. In the query-by-example image retrieval task, we show a significant improvement in Mean Average Precision and the precision of the top 10 images compared to a bag-of-terms approach. We also perform a correlation analysis of human judgements against automatic evaluation measures for the image description task. The automatic measures are standard measures adopted from the machine translation and summarization literature. The main finding of the analysis is that unigram BLEU is less correlated with human judgements than Smoothed BLEU, Meteor, or skip-bigram ROUGE.

In this thesis, we compare the description length of different grammars, and extend the research of automatic grammar learning to the grammar production of Stanford parser. In our research before, we have introduced that how to minimize the description length of the grammar which is generated from the Academia Sinica Balanced Corpus. Based on the concept of data compression, the encoding method in our research is effective in reducing the description length of a text corpus. Moreover, we further discussed about the description length of two special cases of context-free grammars: exhaustive and recursive. The exhaustive grammar is that for every distinct sentence in the corpus is derived, and the recursive one covers all strings. In our research of this thesis, we use a parsing tool called "Stanford parser" to parse sentences and generate grammar rules. We also compare the description length of the grammar parsed by machine with the grammar fixed by artificial. In one of the experiments, we use Stanford parser to parse ASBC corpus, and the description length is 53.0Mb. The description length of rule is only 52,683. In the other experiment, we use Stanford parser to parse Sinica Treebank and compare the description length of the generated grammar with the origin. The result shows that the description length of grammar of the Sinica Treebank is 2.76Mb, and the grammar generated by Stanford parser is 4.02Mb.

In this thesis a natural language query interface is developed for semantic and spatio-temporal querying of MPEG-7 based domain ontologies. The underlying ontology is created by attaching domain ontologies to the core Rhizomik MPEG-7 ontology. The user can pose concept, complex concept (objects connected with an &ldquo / AND&rdquo / or &ldquo / OR&rdquo / connector), spatial (left, right . . . ), temporal (before, after, at least 10 minutes before, 5 minutes after . . . ), object trajectory and directional trajectory (east, west, southeast . . . , left, right, upwards . . . ) queries to the system. Furthermore, the system handles the negative meaning in the user input. When the user enters a natural language (NL) input, it is parsed with the link parser. According to query type, the objects, attributes, spatial relation, temporal relation, trajectory relation, time filter and time information are extracted from the parser output by using predefined rules. After the information extraction, SPARQL queries are generated, and executed against the ontology by using an RDF API. Results are retrieved and they are used to calculate spatial, temporal, and trajectory relations between objects. The results satisfying the required relations are displayed in a tabular format and user can navigate through the multimedia content.

Zentrale Zielstellung dieser Arbeit ist die Entwicklung eines Konzepts für ein Prozessdatenmanagementsystem für Klein- und Mittelständische Unternehmen. Dies umfasst sowohl die Problematik der prozessgebundenen Massendatenerfassung mit Hilfe einer Datenbank als auch eine einfache, flexible und interoperable Kommunikation zwischen Datenbank, Prozessdatenquellen und Datenbankanwendungen. Eine besondere Schwierigkeit besteht darin, Datenbanktransaktionen unter prozessbedingten Echtzeitanforderungen im Dauerbetrieb und ausfallsicher abzuwickeln. Das entwickelte Konzept beinhaltet folgende wichtigen Funktionalitäten: Socketbasierte ASCII-Textübertragung, 4GL mit speziellen Ausdrucksmitteln und Anwendungsbeschreibungssprache, Priorisiertes Ereignis- und Transaktionsmanagement, Spezielle Indizes und Zeiger, Replikationsverfahren zur Sicherstellung von hoher Verfügbarkeit und Performance sowie Mechanismen zur Softwarewartung und -änderung bei laufendem Betrieb.

Lithuanian language is quite in an early stage of language processing. And therefore has a high demand on automated tools like taggers, parsers, word sense disambiguators etc. During the last 10 years only a few researchers were attempting to create a parser for Lithuanian language. However none of them are used in practices nowadays. The process of designing and implementing rule based parser for Lithuanian language is presented in this paper. Rules and constraints of the formal grammar follow the principles of Dependency Grammar. Necessary language recourses were made up at the Computational Centre of Linguistics. Research area analysis and overview of the most popular methodologies is presented here as well. Syntax parser of the Lithuanian language was evaluated against the Gold Standard and gave 80,2 % of accuracy of in recognizing parts of the sentence.

The theme of this thesis is syntax analysis of the source texts based on TeX. The work contains the summary of basic terms from the theory of formal languages, there is also explained the function of the translator in all the analytical phases of the translation and finally it contains the introduction of the Lua scripting language and the ConTeXt typesetting system. The aim of the thesis is implementation of the syntax analyser for the source texts in ConTEXt format. The implementation is accompanied by the description of the solution developement of the lexical analysis, syntax analysis, creating syntax diagrams and context-free grammar.

In the field of software engineering, software architecture plays an important role particularly in areas of critical and large-scale software system development and over the years it has evolved as an important sub-discipline within the field of software engineering. However, software architecture is still an emerging discipline mainly attributed by the lack of standardized way for architectural representation and also due to lack of analysis methods that can determine if the intended architecture translates into correct implementation during the software development [HNS00]. Architecture compliance checking [KP07] is a technique used to resolve latter part of the problem and Fraunhofer SAVE (Software Architecture Visualization and Evaluation) is a compliance-checking tool that uses fact extraction. This master’s thesis provides fact extraction support to Fraunhofer SAVE for a system developed using Ruby on Rail framework by developing a fact extractor. The fact extractor was developed as an eclipse plug-in in Java that was integrated with SAVE platform, it consists of a parser that parses Ruby source code and then generates an abstract syntax tree. The architectural facts are extracted by analyzing these abstract syntax trees using a visitor pattern from which architecture of the system are generated. It is represented using the internal model of the SAVE platform. The fact extractor was validated using two reference systems of differing sizes developed using Ruby on Rails framework. A reference system with smaller size, which contains all the relevant Ruby language constructs, was used to evaluate correctness and completeness of the fact extractor. The evaluation result showed the correctness value of 1.0 or 100% and completeness value of 1.0 or 100%. Afterwards, a larger application with more complex architecture was used to validate the performance and robustness of the fact extractor. It has successfully extracted, analyzed and build the SAVE model of this large system by taking 0.05 seconds per component without crashing. Based these computations, it was concluded that the performance of the fact extractor was acceptable as it performed better than C# fact extractor.

Title: Kind parser generator Author: Bc. Tomáš Dzurenko Department: Network and Labs Management Center Supervisor: RNDr. Michal Žemlička, Ph.D., Department of Software and Com- puter Science Education Abstract: This thesis introduces a generator which takes as its input a definition k-kind grammar and creates source code of analyzer or translator for the language generated by this kind grammar. Opposed to traditional LL(k) grammars, k-kind grammars allow usage of direct left recursion in its rules. This allows for more comfortable and clearer formulation of input grammar rules. Keywords: parser, translator, generator, C++, kind grammar

This project deals with a web-based lecture browser, whose goal is to simplify the gaining of knowledge with the use of multimedia. It presents an existing lecture browser that was created for a diploma thesis at FIT VUT Brno. Demonstrated are the technologies that are used and which will be used to migrate the browser to a MySQL database and to develop a transcription module for speeches. The reader will be acquainted with an analysis and model of the new application. Furthermore, implementation methods for development and subsequent testing are discussed. At the end of the project is a conclusion about the future development of web-based lecture browsers.

This Master's thesis describes design and implementation of advanced web crawler. This crawler can be configured by user and is designed for web browsing according to specified parameters. Can acquire and evaluate content of web pages. Its configuration is performed by creating projects which are consisting of different types of steps. User can create simple action like downloading page, form submission, etc. or can create more complex and larger projects.