989 resultados para RDF,Named Graphs,Provenance,Semantic Web,Semantics
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From where did this tweet originate? Was this quote from the New York Times modified? Daily, we rely on data from the Web but often it is difficult or impossible to determine where it came from or how it was produced. This lack of provenance is particularly evident when people and systems deal with Web information or with any environment where information comes from sources of varying quality. Provenance is not captured pervasively in information systems. There are major technical, social, and economic impediments that stand in the way of using provenance effectively. This paper synthesizes requirements for provenance on the Web for a number of dimensions focusing on three key aspects of provenance: the content of provenance, the management of provenance records, and the uses of provenance information. To illustrate these requirements, we use three synthesized scenarios that encompass provenance problems faced by Web users today.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Considering the context that integrates the internet and the information, the present paper has aimed to analyze the content from the juridical portal named Migalhas, more specifically the daily information–newsletter that is sent to its readers. Starting by the passage on the pathway of the internet, cyber culture and web journalism, and some concepts of news production, it is aimed to describe and evaluate, from the content of the proposed analyzes by Laurence Bardin, about general aspects, strategies and bulletin samples. Bringing a little of its history and description of the journalistic and news main points. The present paper approaches how these criteria, news value, and tools are chosen and used to reach the effectiveness of the proposal to take specific and fast information to the readers. Questions regarded to the opinionated character from the content were also stated as a way to evaluate its expressiveness
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The classification of texts has become a major endeavor with so much electronic material available, for it is an essential task in several applications, including search engines and information retrieval. There are different ways to define similarity for grouping similar texts into clusters, as the concept of similarity may depend on the purpose of the task. For instance, in topic extraction similar texts mean those within the same semantic field, whereas in author recognition stylistic features should be considered. In this study, we introduce ways to classify texts employing concepts of complex networks, which may be able to capture syntactic, semantic and even pragmatic features. The interplay between various metrics of the complex networks is analyzed with three applications, namely identification of machine translation (MT) systems, evaluation of quality of machine translated texts and authorship recognition. We shall show that topological features of the networks representing texts can enhance the ability to identify MT systems in particular cases. For evaluating the quality of MT texts, on the other hand, high correlation was obtained with methods capable of capturing the semantics. This was expected because the golden standards used are themselves based on word co-occurrence. Notwithstanding, the Katz similarity, which involves semantic and structure in the comparison of texts, achieved the highest correlation with the NIST measurement, indicating that in some cases the combination of both approaches can improve the ability to quantify quality in MT. In authorship recognition, again the topological features were relevant in some contexts, though for the books and authors analyzed good results were obtained with semantic features as well. Because hybrid approaches encompassing semantic and topological features have not been extensively used, we believe that the methodology proposed here may be useful to enhance text classification considerably, as it combines well-established strategies. (c) 2012 Elsevier B.V. All rights reserved.
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[ES] Este Trabajo de Fin de Grado es un servicio basado en tecnologías web. El objetivo principal es ofrecer un servicio de creación y gestión de actas para el Ayuntamiento de Las Palmas de Gran Canaria. Para ello, consta de dos módulos principales, uno para “crear actas” y otro para “editar actas”. También se ha desarrollado otro módulo llamado plantillas donde se genera un PDF a partir de una plantilla preestablecida. Esta aplicación ha sido dividida en diferentes partes. La primera parte consistió en generar todas las configuraciones de base de datos necesarias para el funcionamiento de la aplicación. Después generamos todos los ficheros HTML y las interconexiones entre ellos. Finalmente, dotamos a esos HTML estáticos de un estilo mucho más claro y organizado, dando a la aplicación una apariencia mucho más bonita. Una vez finalizada la parte frontal de la aplicación, empezamos a implementar la lógica detrás de la aplicación. Los módulos de “crear” y “editar” se hicieron utilizando formularios HTML y combinando la información obtenida de esos formularios con unas plantillas HTML generadas por nosotros. Toda esa información obtenida de los formularios se guarda en unos ficheros .txt para poder ser utilizados por el módulo editar. El módulo de plantillas nos muestra un editor HTML rellenado con una plantilla que ha sido previamente seleccionada por el usuario. Los ficheros pdf de este módulo no pueden editados con posterioridad por lo que no se generan ficheros .txt. Por último, hay dos módulos que nos permiten ver todas las actas generadas por la aplicación. El primero de los dos módulos es el módulo de búsqueda, que nos permite buscar una palabra clave dentro de todos los ficheros pdf. El otro módulo nos muestra todas las actas que han sido marcadas como “cerradas”. Esta aplicación ha sido diseñada de forma modular, de manera que podemos añadir o quitar módulos de manera sencilla.
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Il lavoro svolto in questa tesi è stato quello di analizzare il Web Semantico e i suoi linguaggi di rappresentazione delle informazioni. Inoltre sono state introdotte le ontologie evidenziando il loro ruolo all’interno del Web Semantico. Infine è stato fatto uno studio riguardo le ontologie attualmente sviluppate, allo scopo di portare a termine un’analisi comparativa delle stesse.
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La trattazione di questa tesi ha lo scopo di fornire esempi di ontologie, nonché una panoramica sugli editor per la creazione e lo sviluppo di queste, evidenziandone pregi e difetti. Dopo un’introduzione generale al Web Semantico, tale documento fornisce dei tutorial, sempre affiancati da molteplici screenshot e da tutto il codice necessario, molto utili per “avventurarsi” nello sviluppo di ontologie. Le ontologie, per essere fruibili, devono essere pubblicate. Si è deciso pertanto di dare una descrizione dei principali vocabolari attualmente utilizzati nell’ambito del Web Semantico, così da dare un’idea al lettore dei diversi tipi di vocabolario presenti sul web. Infine è stato esaminato Jena: un framework per le applicazioni del Web Semantico sviluppate in Java. Anche in questo caso è stato creato un tutorial in cui tale framework è stato integrato in Eclipse. Vengono mostrati l’installazione delle librerie, l’importazione e l’interrogazione di un file RDF. Poiché per importare un file RDF il lettore deve averne uno, è stata colta l’occasione per fornire anche una guida utile alla creazione di un documento RDF, attraverso FOAF-a-Matic, un’applicazione Javascript che permette di creare una descrizione di se stessi in formato FOAF.
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This thesis aims at investigating methods and software architectures for discovering what are the typical and frequently occurring structures used for organizing knowledge in the Web. We identify these structures as Knowledge Patterns (KPs). KP discovery needs to address two main research problems: the heterogeneity of sources, formats and semantics in the Web (i.e., the knowledge soup problem) and the difficulty to draw relevant boundary around data that allows to capture the meaningful knowledge with respect to a certain context (i.e., the knowledge boundary problem). Hence, we introduce two methods that provide different solutions to these two problems by tackling KP discovery from two different perspectives: (i) the transformation of KP-like artifacts to KPs formalized as OWL2 ontologies; (ii) the bottom-up extraction of KPs by analyzing how data are organized in Linked Data. The two methods address the knowledge soup and boundary problems in different ways. The first method provides a solution to the two aforementioned problems that is based on a purely syntactic transformation step of the original source to RDF followed by a refactoring step whose aim is to add semantics to RDF by select meaningful RDF triples. The second method allows to draw boundaries around RDF in Linked Data by analyzing type paths. A type path is a possible route through an RDF that takes into account the types associated to the nodes of a path. Then we present K~ore, a software architecture conceived to be the basis for developing KP discovery systems and designed according to two software architectural styles, i.e, the Component-based and REST. Finally we provide an example of reuse of KP based on Aemoo, an exploratory search tool which exploits KPs for performing entity summarization.
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Traditionally, ontologies describe knowledge representation in a denotational, formalized, and deductive way. In addition, in this paper, we propose a semiotic, inductive, and approximate approach to ontology creation. We define a conceptual framework, a semantics extraction algorithm, and a first proof of concept applying the algorithm to a small set of Wikipedia documents. Intended as an extension to the prevailing top-down ontologies, we introduce an inductive fuzzy grassroots ontology, which organizes itself organically from existing natural language Web content. Using inductive and approximate reasoning to reflect the natural way in which knowledge is processed, the ontology’s bottom-up build process creates emergent semantics learned from the Web. By this means, the ontology acts as a hub for computing with words described in natural language. For Web users, the structural semantics are visualized as inductive fuzzy cognitive maps, allowing an initial form of intelligence amplification. Eventually, we present an implementation of our inductive fuzzy grassroots ontology Thus,this paper contributes an algorithm for the extraction of fuzzy grassroots ontologies from Web data by inductive fuzzy classification.
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Web-scale knowledge retrieval can be enabled by distributed information retrieval, clustering Web clients to a large-scale computing infrastructure for knowledge discovery from Web documents. Based on this infrastructure, we propose to apply semiotic (i.e., sub-syntactical) and inductive (i.e., probabilistic) methods for inferring concept associations in human knowledge. These associations can be combined to form a fuzzy (i.e.,gradual) semantic net representing a map of the knowledge in the Web. Thus, we propose to provide interactive visualizations of these cognitive concept maps to end users, who can browse and search the Web in a human-oriented, visual, and associative interface.
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En esta tesis se trabaja sobre la hipótesis de que el componente didáctico del discurso divulgativo queda delimitado por estrategias discursivas originadas en el tratamiento modal y actualizadas en los niveles funcional, situacional, semántico y formal-gramatical. El objetivo es caracterizar tales estrategias para identificar tendencias en la realización lingüísticodiscursiva del componente didáctico. El corpus se ha formado teniendo en cuenta soporte (web), formato (hipertexto) y dominio disciplinar (Análisis Sensorial de Vinos). La metodología es, fundamentalmente, cualitativo-ejemplar, basada en el modelo multinivel propuesto por Ciapuscio (2003) para el análisis de textos especializados. Los resultados sugieren que en el nivel funcional, el componente didáctico se distingue por el predominio de los términos positivos de las categorías modales epistémica (función informar) y ética (función dirigir); en el nivel situacional, por tres tipos de construcciones discursivas: la del enunciador experto, la del enunciatario lego y la de la pertenencia del lego a la comunidad especializada; en el nivel semántico, por la estandarización de partes textuales y por el predominio tanto de axiologización eufórica ética y cognoscitiva, como de secuencias expositivas y de procedimientos explicativos causales, descriptivos e ilustrativos; en el nivel formal, por recursos paratextuales e hipertextuales que refuerzan la actualización del componente didáctico.