573 research outputs found

    Computer Science and Technology Series : XV Argentine Congress of Computer Science. Selected papers

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    CACIC'09 was the fifteenth Congress in the CACIC series. It was organized by the School of Engineering of the National University of Jujuy. The Congress included 9 Workshops with 130 accepted papers, 1 main Conference, 4 invited tutorials, different meetings related with Computer Science Education (Professors, PhD students, Curricula) and an International School with 5 courses. CACIC 2009 was organized following the traditional Congress format, with 9 Workshops covering a diversity of dimensions of Computer Science Research. Each topic was supervised by a committee of three chairs of different Universities. The call for papers attracted a total of 267 submissions. An average of 2.7 review reports were collected for each paper, for a grand total of 720 review reports that involved about 300 different reviewers. A total of 130 full papers were accepted and 20 of them were selected for this book.Red de Universidades con Carreras en Informática (RedUNCI

    Computer Science and Technology Series : XV Argentine Congress of Computer Science. Selected papers

    Get PDF
    CACIC'09 was the fifteenth Congress in the CACIC series. It was organized by the School of Engineering of the National University of Jujuy. The Congress included 9 Workshops with 130 accepted papers, 1 main Conference, 4 invited tutorials, different meetings related with Computer Science Education (Professors, PhD students, Curricula) and an International School with 5 courses. CACIC 2009 was organized following the traditional Congress format, with 9 Workshops covering a diversity of dimensions of Computer Science Research. Each topic was supervised by a committee of three chairs of different Universities. The call for papers attracted a total of 267 submissions. An average of 2.7 review reports were collected for each paper, for a grand total of 720 review reports that involved about 300 different reviewers. A total of 130 full papers were accepted and 20 of them were selected for this book.Red de Universidades con Carreras en Informática (RedUNCI

    CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

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    Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

    Engines of Order

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    Over the last decades, and in particular since the widespread adoption of the Internet, encounters with algorithmic procedures for ‘information retrieval’ – the activity of getting some piece of information out of a col-lection or repository of some kind – have become everyday experiences for most people in large parts of the world

    Macro- and microscopic analysis of the internet economy from network measurements

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    Tesi per compendi de publicacions.The growth of the Internet impacts multiple areas of the world economy, and it has become a permanent part of the economic landscape both at the macro- and at microeconomic level. On-line traffic and information are currently assets with large business value. Even though commercial Internet has been a part of our lives for more than two decades, its impact on global, and everyday, economy still holds many unknowns. In this work we analyse important macro- and microeconomic aspects of the Internet. First we investigate the characteristics of the interdomain traffic, which is an important part of the macroscopic economy of the Internet. Finally, we investigate the microeconomic phenomena of price discrimination in the Internet. At the macroscopic level, we describe quantitatively the interdomain traffic matrix (ITM), as seen from the perspective of a large research network. The ITM describes the traffic flowing between autonomous systems (AS) in the Internet. It depicts the traffic between the largest Internet business entities, therefore it has an important impact on the Internet economy. In particular, we analyse the sparsity and statistical distribution of the traffic, and observe that the shape of the statistical distribution of the traffic sourced from an AS might be related to congestion within the network. We also investigate the correlations between rows in the ITM. Finally, we propose a novel method to model the interdomain traffic, that stems from first-principles and recognizes the fact that the traffic is a mixture of different Internet applications, and can have regional artifacts. We present and evaluate a tool to generate such matrices from open and available data. Our results show that our first-principles approach is a promising alternative to the existing solutions in this area, which enables the investigation of what-if scenarios and their impact on the Internet economy. At the microscopic level, we investigate the rising phenomena of price discrimination (PD). We find empirical evidences that Internet users can be subject to price and search discrimination. In particular, we present examples of PD on several ecommerce websites and uncover the information vectors facilitating PD. Later we show that crowd-sourcing is a feasible method to help users to infer if they are subject to PD. We also build and evaluate a system that allows any Internet user to examine if she is subject to PD. The system has been deployed and used by multiple users worldwide, and uncovered more examples of PD. The methods presented in the following papers are backed with thorough data analysis and experiments.Internet es hoy en día un elemento crucial en la economía mundial, su constante crecimiento afecta directamente múltiples aspectos tanto a nivel macro- como a nivel microeconómico. Entre otros aspectos, el tráfico de red y la información que transporta se han convertido en un producto de gran valor comercial para cualquier empresa. Sin embargo, más de dos decadas después de su introducción en nuestras vidas y siendo un elemento de vital importancia, el impacto de Internet en la economía global y diaria es un tema que alberga todavía muchas incógnitas que resolver. En esta disertación analizamos importantes aspectos micro y macroeconómicos de Internet. Primero, investigamos las características del tráfico entre Sistemas Autónomos (AS), que es un parte decisiva de la macroeconomía de Internet. A continuacin, estudiamos el controvertido fenómeno microeconómico de la discriminación de precios en Internet. A nivel macroeconómico, mostramos cuantitatívamente la matriz del tráfico entre AS ("Interdomain Traffic Matrix - ITM"), visto desde la perspectiva de una gran red científica. La ITM obtenida empíricamente muestra la cantidad de tráfico compartido entre diferentes AS, las entidades más grandes en Internet, siendo esto uno de los principales aspectos a evaluar en la economiá de Internet. Esto nos permite por ejemplo, analizar diferentes propiedades estadísticas del tráfico para descubrir si la distribución del tráfico producido por un AS está directamente relacionado con la congestión dentro de la red. Además, este estudio también nos permite investigar las correlaciones entre filas de la ITM, es decir, entre diferentes AS. Por último, basándonos en el estudio empírico, proponemos una innovadora solución para modelar el tráfico en una ITM, teniendo en cuenta que el tráfico modelado es dependiente de las particularidades de cada escenario (e.g., distribución de apliaciones, artefactos). Para obtener resultados representativos, la herramienta propuesta para crear estas matrices es evaluada a partir de conjuntos de datos abiertos, disponibles para toda la comunidad científica. Los resultados obtenidos muestran que el método propuesto es una prometedora alternativa a las soluciones de la literatura. Permitiendo así, la nueva investigación de escenarios desconocidos y su impacto en la economía de Internet. A nivel microeconómico, en esta tesis investigamos el fenómeno de la discriminación de precios en Internet ("price discrimination" - PD). Nuestros estudios permiten mostrar pruebas empíricas de que los usuarios de Internet están expuestos a discriminación de precios y resultados de búsquedas. En particular, presentamos ejemplos de PD en varias páginas de comercio electrónico y descubrimos que informacin usan para llevarlo a cabo. Posteriormente, mostramos como una herramienta crowdsourcing puede ayudar a la comunidad de usuarios a inferir que páginas aplican prácticas de PD. Con el objetivo de mitigar esta cada vez más común práctica, publicamos y evaluamos una herramienta que permite al usuario deducir si está siendo víctima de PD. Esta herramienta, con gran repercusión mediática, ha sido usada por multitud de usuarios alrededor del mundo, descubriendo así más ejemplos de discriminación. Por último remarcar que todos los metodos presentados en esta disertación están respaldados por rigurosos análisis y experimentos.Postprint (published version

    CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

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    After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

    Modeling Non-Standard Text Classification Tasks

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    Text classification deals with discovering knowledge in texts and is used for extracting, filtering, or retrieving information in streams and collections. The discovery of knowledge is operationalized by modeling text classification tasks, which is mainly a human-driven engineering process. The outcome of this process, a text classification model, is used to inductively learn a text classification solution from a priori classified examples. The building blocks of modeling text classification tasks cover four aspects: (1) the way examples are represented, (2) the way examples are selected, (3) the way classifiers learn from examples, and (4) the way models are selected. This thesis proposes methods that improve the prediction quality of text classification solutions for unseen examples, especially for non-standard tasks where standard models do not fit. The original contributions are related to the aforementioned building blocks: (1) Several topic-orthogonal text representations are studied in the context of non-standard tasks and a new representation, namely co-stems, is introduced. (2) A new active learning strategy that goes beyond standard sampling is examined. (3) A new one-class ensemble for improving the effectiveness of one-class classification is proposed. (4) A new model selection framework to cope with subclass distribution shifts that occur in dynamic environments is introduced

    Vertrauensbasierte Empfehlungen in mehrschichtigen Netzwerken

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    The huge interest in social networking applications - Friendster.com, for example, has more than 40 million users - led to a considerable research interest in using this data for generating recommendations. Especially recommendation techniques that analyze trust networks were found to provide very accurate and highly personalized results. The main contribution of this thesis is to extend the approach to trust-based recommendations, which up to now have been made for unlinked items such as products or movies, to linked resources, in particular documents. Therefore, a second type of network, namely a document reference network, is considered apart from the trust network. This is, for example, the citation network of scientific publications or the hyperlink graph of webpages. Recommendations for documents are typically made by reference-based visibility measures which consider a document to be the more important, the more often it is referenced by important documents. Document and trust networks, as well as further networks such as organization networks are integrated in a multi-layer network. This architecture makes it possible to combine classical measures for the visibility of a document with trust-based recommendations, giving trust-enhanced visibility measures. Moreover, an approximation approach is introduced which considers the uncertainty induced by duplicate documents. These measures are evaluated in simulation studies. The trust-based recommender system for scientific publications SPRec implements a two-layer architecture and provides personalized recommendations via a Web interface.Soziale Netzwerke mit ihren Millionen von Nutzern haben zu einem großen Interesse an der Fragestellung geführt, wie die Informationen aus solchen sozialen Netzwerken in Empfehlungssystemen genutzt werden können. Aktuelle Forschungsarbeiten haben gezeigt, dass vor allem Techniken, die soziale Vertrauensnetzwerke zur Grundlage nehmen, sehr gute Ergebnisse liefern. Die vorliegende Dissertation erweitert Ansätze zu vertrauensbasierten Empfehlungen, die bisher nur isolierte Objekte wie beispielsweise Produkte oder Filme berücksichtigt haben, zu Ansätzen für vernetzte Ressourcen, insbesondere Dokumente. Daher wird neben dem Vertrauensnetzwerk eine zweite Art von Netzwerk betrachtet, ein Dokumentennetzwerk. Beispiele für Dokumentennetzwerke sind Zitationsnetzwerke wissenschaftlicher Publikationen oder der Hyperlink-Graph zwischen Webseiten. Dokumentenempfehlungen werden typischerweise mit referenzbasierten Sichtbarkeitsmaßen berechnet, die ein Dokument als wichtig erachten, wenn es von vielen wichtigen Dokumenten referenziert wird. Vertrauensnetzwerke und Dokumentennetzwerke werden in einer zweischichtigen Architektur integriert. Weitere Netzwerke, wie zum Beispiel Organisationsnetzwerke bauen sie zu einer mehrschichtigen Architektur aus. In dieser Architektur können klassische Maße für Dokumentensichtbarkeit mit vertrauensbasierten Empfehlungen kombiniert werden, nämlich in den sogenannten vertrauensbasierten Sichtbarkeitsmaßen. Darüberhinaus führt die Dissertation einen Ansatz ein, um die vertrauensbasierte Sichtbarkeit dann approximieren zu können, wenn das Dokumentennetzwerk Duplikate von Dokumenten enthält. Die entwickelten Sichtbarkeitsmaße werden in einer Simulationsstudie analysiert. Das webbasierte Empfehlungssystem für wissenschaftliche Veröffentlichungen SPRec implementiert die vertrauensbasierten Sichtbarkeitsmaße und generiert personalisierte Empfehlungen
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