609 research outputs found

    Proximal business intelligence on the semantic web

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    This is the post-print version of this article. The official version can be accessed from the link below - Copyright @ 2010 Springer.Ubiquitous information systems (UBIS) extend current Information System thinking to explicitly differentiate technology between devices and software components with relation to people and process. Adapting business data and management information to support specific user actions in context is an ongoing topic of research. Approaches typically focus on providing mechanisms to improve specific information access and transcoding but not on how the information can be accessed in a mobile, dynamic and ad-hoc manner. Although web ontology has been used to facilitate the loading of data warehouses, less research has been carried out on ontology based mobile reporting. This paper explores how business data can be modeled and accessed using the web ontology language and then re-used to provide the invisibility of pervasive access; uncovering more effective architectural models for adaptive information system strategies of this type. This exploratory work is guided in part by a vision of business intelligence that is highly distributed, mobile and fluid, adapting to sensory understanding of the underlying environment in which it operates. A proof-of concept mobile and ambient data access architecture is developed in order to further test the viability of such an approach. The paper concludes with an ontology engineering framework for systems of this type – named UBIS-ONTO

    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

    Report of the Stanford Linked Data Workshop

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    The Stanford University Libraries and Academic Information Resources (SULAIR) with the Council on Library and Information Resources (CLIR) conducted at week-long workshop on the prospects for a large scale, multi-national, multi-institutional prototype of a Linked Data environment for discovery of and navigation among the rapidly, chaotically expanding array of academic information resources. As preparation for the workshop, CLIR sponsored a survey by Jerry Persons, Chief Information Architect emeritus of SULAIR that was published originally for workshop participants as background to the workshop and is now publicly available. The original intention of the workshop was to devise a plan for such a prototype. However, such was the diversity of knowledge, experience, and views of the potential of Linked Data approaches that the workshop participants turned to two more fundamental goals: building common understanding and enthusiasm on the one hand and identifying opportunities and challenges to be confronted in the preparation of the intended prototype and its operation on the other. In pursuit of those objectives, the workshop participants produced:1. a value statement addressing the question of why a Linked Data approach is worth prototyping;2. a manifesto for Linked Libraries (and Museums and Archives and …);3. an outline of the phases in a life cycle of Linked Data approaches;4. a prioritized list of known issues in generating, harvesting & using Linked Data;5. a workflow with notes for converting library bibliographic records and other academic metadata to URIs;6. examples of potential “killer apps” using Linked Data: and7. a list of next steps and potential projects.This report includes a summary of the workshop agenda, a chart showing the use of Linked Data in cultural heritage venues, and short biographies and statements from each of the participants

    Surveillance Video for Mobile Devices

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    In this paper, we present a video encoding scheme that uses object-based adaptation to deliver surveillance video to mobile devices. The method relies on a set of complementary video adaptation strategies and generates content that matches various appliance and network resources. Prior to encoding, some of the adaptation strategies exploit video object segmentation and selective filtering in order to improve the perceived quality. Moreover, object segmentation enables the generation of automatic summaries and of simplified versions of the monitored scene. The performance of individual adaptation strategies is assessed using an objective video quality metric, which is also used to select the strategy that provides maximum value for the user under a given set of constraints. We demonstrate the effectiveness of the scheme on standard surveillance test sequences and realistic mobile client resource profiles

    Adaptive video delivery using semantics

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    The diffusion of network appliances such as cellular phones, personal digital assistants and hand-held computers has created the need to personalize the way media content is delivered to the end user. Moreover, recent devices, such as digital radio receivers with graphics displays, and new applications, such as intelligent visual surveillance, require novel forms of video analysis for content adaptation and summarization. To cope with these challenges, we propose an automatic method for the extraction of semantics from video, and we present a framework that exploits these semantics in order to provide adaptive video delivery. First, an algorithm that relies on motion information to extract multiple semantic video objects is proposed. The algorithm operates in two stages. In the first stage, a statistical change detector produces the segmentation of moving objects from the background. This process is robust with regard to camera noise and does not need manual tuning along a sequence or for different sequences. In the second stage, feedbacks between an object partition and a region partition are used to track individual objects along the frames. These interactions allow us to cope with multiple, deformable objects, occlusions, splitting, appearance and disappearance of objects, and complex motion. Subsequently, semantics are used to prioritize visual data in order to improve the performance of adaptive video delivery. The idea behind this approach is to organize the content so that a particular network or device does not inhibit the main content message. Specifically, we propose two new video adaptation strategies. The first strategy combines semantic analysis with a traditional frame-based video encoder. Background simplifications resulting from this approach do not penalize overall quality at low bitrates. The second strategy uses metadata to efficiently encode the main content message. The metadata-based representation of object's shape and motion suffices to convey the meaning and action of a scene when the objects are familiar. The impact of different video adaptation strategies is then quantified with subjective experiments. We ask a panel of human observers to rate the quality of adapted video sequences on a normalized scale. From these results, we further derive an objective quality metric, the semantic peak signal-to-noise ratio (SPSNR), that accounts for different image areas and for their relevance to the observer in order to reflect the focus of attention of the human visual system. At last, we determine the adaptation strategy that provides maximum value for the end user by maximizing the SPSNR for given client resources at the time of delivery. By combining semantic video analysis and adaptive delivery, the solution presented in this dissertation permits the distribution of video in complex media environments and supports a large variety of content-based applications

    ViSOR: VIdeo Surveillance On-line Repository for annotation retrieval

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    Aim of the Visor Project [1] is to gather and make freely available a repository of surveillance and video footages for the research community on pattern recognition and multimedia retrieval. Th

    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

    MIRACLE at NTCIR-7 MOAT: First experiments on multilingual opinion analysis

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    This paper describes the participation of MIRACLE research consortium at NTCIR-7 Multilingual Opinion Analysis Task, our first attempt on sentiment analysis and second on East Asian languages. We took part in the main mandatory opinionated sentence judgment subtask (to decide whether each sentence expresses an opinion or not) and the optional relevance and polarity judgment subtasks (to decide whether a given sentence is relevant to the given topic and also the polarity of the expressed opinion). Our approach combines a semantic languagedependent tagging of the terms of the sentence and the topic and three different ad-hoc classifiers that provide the specific annotation for each subtask, run in cascade. These models have been trained with the corpus provided in NTCIR-6 Opinion Analysis pilot task

    The Semantic Shadow : Combining User Interaction with Context Information for Semantic Web-Site Annotation

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    This thesis develops the concept of the Semantic Shadow (SemS), a model for managing contentual and structural annotations on web page elements and their values. The model supports a contextual weighting of the annotated information, allowing to specify the annotation values in relation to the evaluation context. A procedure is presented, which allows to manage and process this context-dependent meta information on web page elements using a dedicated programming interface. Two distinct implementations for the model have been developed: One based on Java objects, the other using the Resource Description Framework (RDF) as modeling backend. This RDF-based storage allows to integrate the annotations of the Semantic Shadow with other information of the Semantic Web. To demonstrate the application of the Semantic Shadow concept, a procedure to optimize web based user interfaces based on the structural semantics has been developed: Assuming a mobile client, a requested web page is dynamically adapted by a proxy prototype, where the context-awareness of the adaptation can be directly modeled alongside with the structural annotations. To overcome the drawback of missing annotations for existing web pages, this thesis introduces a concept to derive context-dependent meta-information on the web pages from their usage: From the observation of the users' interaction with a web page, certain context-dependent structural information about the concerned web page elements can be derived and stored in the annotation model of the Semantic Shadow concept.In dieser Arbeit wird das Konzept des Semantic Shadow (dt. Semantischer Schatten) entwickelt, ein Programmier-Modell um Webseiten-Elemente mit inhaltsbezogenen und strukturellen Anmerkungen zu versehen. Das Modell unterstützt dabei eine kontextabhängige Gewichtung der Anmerkungen, so dass eine Anmerkung in Bezug zum Auswertungs-Kontext gesetzt werden kann. Zur Verwaltung und Verarbeitung dieser kontextbezogenen Meta-Informationen für Webseiten-Elemente wurde im Rahmen der Arbeit eine Programmierschnittstelle definiert. Dazu wurden zwei Implementierungen der Schnittstelle entwickelt: Eine basiert ausschließlich auf Java-Objekten, die andere baut auf einem RDF-Modell auf. Die RDF-basierte Persistierung erlaubt eine Integration der Semantic-Shadow-Anmerkungen mit anderen Anwendungen des Semantic Webs. Um die Anwendungsmöglichkeiten des Semantic-Shadow-Konzepts darzustellen, wurde eine Vorgehensweise zur Optimierung von webbasierten Benutzerschnittstellen auf Grundlage von semantischen Strukturinformationen entwickelt: Wenn ein mobiler Benutzer eine Webseite anfordert, wird diese dynamisch durch einen Proxy angepasst. Die Kontextabhängigkeit dieser Anpassung wird dabei bereits direkt mit den Struktur-Anmerkungen modelliert. Für bestehende Webseiten liegen zumeist keine Annotationen vor. Daher wird in dieser Arbeit ein Konzept vorgestellt, kontextabhängige Meta-Informationen aus der Benutzung der Webseiten zu bestimmen: Durch Beobachtung der Benutzer-Interaktionen mit den Webseiten-Elementen ist es möglich bestimmte kontextabhängige Strukturinformationen abzuleiten und als Anmerkungen im Modell des Semantic-Shadow-Konzepts zu persistieren

    Tatouage du flux compressé MPEG-4 AVC

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    La présente thèse aborde le sujet de tatouage du flux MPEG-4 AVC sur ses deux volets théoriques et applicatifs en considérant deux domaines applicatifs à savoir la protection du droit d auteur et la vérification de l'intégrité du contenu. Du point de vue théorique, le principal enjeu est de développer un cadre de tatouage unitaire en mesure de servir les deux applications mentionnées ci-dessus. Du point de vue méthodologique, le défi consiste à instancier ce cadre théorique pour servir les applications visées. La première contribution principale consiste à définir un cadre théorique pour le tatouage multi symboles à base de modulation d index de quantification (m-QIM). La règle d insertion QIM a été généralisée du cas binaire au cas multi-symboles et la règle de détection optimale (minimisant la probabilité d erreur à la détection en condition du bruit blanc, additif et gaussien) a été établie. Il est ainsi démontré que la quantité d information insérée peut être augmentée par un facteur de log2m tout en gardant les mêmes contraintes de robustesse et de transparence. Une quantité d information de 150 bits par minutes, soit environ 20 fois plus grande que la limite imposée par la norme DCI est obtenue. La deuxième contribution consiste à spécifier une opération de prétraitement qui permet d éliminer les impactes du phénomène du drift (propagation de la distorsion) dans le flux compressé MPEG-4 AVC. D abord, le problème a été formalisé algébriquement en se basant sur les expressions analytiques des opérations d encodage. Ensuite, le problème a été résolu sous la contrainte de prévention du drift. Une amélioration de la transparence avec des gains de 2 dB en PSNR est obtenueThe present thesis addresses the MPEG-4 AVC stream watermarking and considers two theoretical and applicative challenges, namely ownership protection and content integrity verification.From the theoretical point of view, the thesis main challenge is to develop a unitary watermarking framework (insertion/detection) able to serve the two above mentioned applications in the compressed domain. From the methodological point of view, the challenge is to instantiate this theoretical framework for serving the targeted applications. The thesis first main contribution consists in building the theoretical framework for the multi symbol watermarking based on quantization index modulation (m-QIM). The insertion rule is analytically designed by extending the binary QIM rule. The detection rule is optimized so as to ensure minimal probability of error under additive white Gaussian noise distributed attacks. It is thus demonstrated that the data payload can be increased by a factor of log2m, for prescribed transparency and additive Gaussian noise power. A data payload of 150 bits per minute, i.e. about 20 times larger than the limit imposed by the DCI standard, is obtained. The thesis second main theoretical contribution consists in specifying a preprocessing MPEG-4 AVC shaping operation which can eliminate the intra-frame drift effect. The drift represents the distortion spread in the compressed stream related to the MPEG encoding paradigm. In this respect, the drift distortion propagation problem in MPEG-4 AVC is algebraically expressed and the corresponding equations system is solved under drift-free constraints. The drift-free shaping results in gain in transparency of 2 dB in PSNREVRY-INT (912282302) / SudocSudocFranceF
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