1,371 research outputs found

    Integrating multimedia streams into a distributed computing system

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    Continuous media, such as audio and video, are quickly becoming an integral part of distributed computing environments. A shortcoming of such environments is their lack of support for continuous flows of information. What is missing is the notion of an on-going communication activity with an associated quality of service. This paper describes a model for integrating multimedia flows into a distributed computing system. The model permits explicit bindings to be established between type-checked stream interfaces. The stream binding is represented in the computational model as a first-class object which encapsulates configuration rules and QoS attributes. An operational interface supplied by the binding object allows other objects within the system to manage the binding, to renegotiate QoS parameters, to control the flows across the binding, and to register interest in stream events such as flow reports and communication errors. The in-band stream interface is an abstract C++ wrapper around transport mechanisms that include intra-host IPC and network transport protocols such as TCP and XTP. A prototype implementation of this model is described using the Common Object Request Broker Architecture (CORBA). The implementation environment comprises a local area ATM network with directly attached multimedia peripherals and general purpose workstations

    Knowledge extraction from unstructured data and classification through distributed ontologies

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    The World Wide Web has changed the way humans use and share any kind of information. The Web removed several access barriers to the information published and has became an enormous space where users can easily navigate through heterogeneous resources (such as linked documents) and can easily edit, modify, or produce them. Documents implicitly enclose information and relationships among them which become only accessible to human beings. Indeed, the Web of documents evolved towards a space of data silos, linked each other only through untyped references (such as hypertext references) where only humans were able to understand. A growing desire to programmatically access to pieces of data implicitly enclosed in documents has characterized the last efforts of the Web research community. Direct access means structured data, thus enabling computing machinery to easily exploit the linking of different data sources. It has became crucial for the Web community to provide a technology stack for easing data integration at large scale, first structuring the data using standard ontologies and afterwards linking them to external data. Ontologies became the best practices to define axioms and relationships among classes and the Resource Description Framework (RDF) became the basic data model chosen to represent the ontology instances (i.e. an instance is a value of an axiom, class or attribute). Data becomes the new oil, in particular, extracting information from semi-structured textual documents on the Web is key to realize the Linked Data vision. In the literature these problems have been addressed with several proposals and standards, that mainly focus on technologies to access the data and on formats to represent the semantics of the data and their relationships. With the increasing of the volume of interconnected and serialized RDF data, RDF repositories may suffer from data overloading and may become a single point of failure for the overall Linked Data vision. One of the goals of this dissertation is to propose a thorough approach to manage the large scale RDF repositories, and to distribute them in a redundant and reliable peer-to-peer RDF architecture. The architecture consists of a logic to distribute and mine the knowledge and of a set of physical peer nodes organized in a ring topology based on a Distributed Hash Table (DHT). Each node shares the same logic and provides an entry point that enables clients to query the knowledge base using atomic, disjunctive and conjunctive SPARQL queries. The consistency of the results is increased using data redundancy algorithm that replicates each RDF triple in multiple nodes so that, in the case of peer failure, other peers can retrieve the data needed to resolve the queries. Additionally, a distributed load balancing algorithm is used to maintain a uniform distribution of the data among the participating peers by dynamically changing the key space assigned to each node in the DHT. Recently, the process of data structuring has gained more and more attention when applied to the large volume of text information spread on the Web, such as legacy data, news papers, scientific papers or (micro-)blog posts. This process mainly consists in three steps: \emph{i)} the extraction from the text of atomic pieces of information, called named entities; \emph{ii)} the classification of these pieces of information through ontologies; \emph{iii)} the disambigation of them through Uniform Resource Identifiers (URIs) identifying real world objects. As a step towards interconnecting the web to real world objects via named entities, different techniques have been proposed. The second objective of this work is to propose a comparison of these approaches in order to highlight strengths and weaknesses in different scenarios such as scientific and news papers, or user generated contents. We created the Named Entity Recognition and Disambiguation (NERD) web framework, publicly accessible on the Web (through REST API and web User Interface), which unifies several named entity extraction technologies. Moreover, we proposed the NERD ontology, a reference ontology for comparing the results of these technologies. Recently, the NERD ontology has been included in the NIF (Natural language processing Interchange Format) specification, part of the Creating Knowledge out of Interlinked Data (LOD2) project. Summarizing, this dissertation defines a framework for the extraction of knowledge from unstructured data and its classification via distributed ontologies. A detailed study of the Semantic Web and knowledge extraction fields is proposed to define the issues taken under investigation in this work. Then, it proposes an architecture to tackle the single point of failure issue introduced by the RDF repositories spread within the Web. Although the use of ontologies enables a Web where data is structured and comprehensible by computing machinery, human users may take advantage of it especially for the annotation task. Hence, this work describes an annotation tool for web editing, audio and video annotation in a web front end User Interface powered on the top of a distributed ontology. Furthermore, this dissertation details a thorough comparison of the state of the art of named entity technologies. The NERD framework is presented as technology to encompass existing solutions in the named entity extraction field and the NERD ontology is presented as reference ontology in the field. Finally, this work highlights three use cases with the purpose to reduce the amount of data silos spread within the Web: a Linked Data approach to augment the automatic classification task in a Systematic Literature Review, an application to lift educational data stored in Sharable Content Object Reference Model (SCORM) data silos to the Web of data and a scientific conference venue enhancer plug on the top of several data live collectors. Significant research efforts have been devoted to combine the efficiency of a reliable data structure and the importance of data extraction techniques. This dissertation opens different research doors which mainly join two different research communities: the Semantic Web and the Natural Language Processing community. The Web provides a considerable amount of data where NLP techniques may shed the light within it. The use of the URI as a unique identifier may provide one milestone for the materialization of entities lifted from a raw text to real world object

    Multiple Media Correlation: Theory and Applications

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    This thesis introduces multiple media correlation, a new technology for the automatic alignment of multiple media objects such as text, audio, and video. This research began with the question: what can be learned when multiple multimedia components are analyzed simultaneously? Most ongoing research in computational multimedia has focused on queries, indexing, and retrieval within a single media type. Video is compressed and searched independently of audio, text is indexed without regard to temporal relationships it may have to other media data. Multiple media correlation provides a framework for locating and exploiting correlations between multiple, potentially heterogeneous, media streams. The goal is computed synchronization, the determination of temporal and spatial alignments that optimize a correlation function and indicate commonality and synchronization between media objects. The model also provides a basis for comparison of media in unrelated domains. There are many real-world applications for this technology, including speaker localization, musical score alignment, and degraded media realignment. Two applications, text-to-speech alignment and parallel text alignment, are described in detail with experimental validation. Text-to-speech alignment computes the alignment between a textual transcript and speech-based audio. The presented solutions are effective for a wide variety of content and are useful not only for retrieval of content, but in support of automatic captioning of movies and video. Parallel text alignment provides a tool for the comparison of alternative translations of the same document that is particularly useful to the classics scholar interested in comparing translation techniques or styles. The results presented in this thesis include (a) new media models more useful in analysis applications, (b) a theoretical model for multiple media correlation, (c) two practical application solutions that have wide-spread applicability, and (d) Xtrieve, a multimedia database retrieval system that demonstrates this new technology and demonstrates application of multiple media correlation to information retrieval. This thesis demonstrates that computed alignment of media objects is practical and can provide immediate solutions to many information retrieval and content presentation problems. It also introduces a new area for research in media data analysis

    MediaSync: Handbook on Multimedia Synchronization

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    This book provides an approachable overview of the most recent advances in the fascinating field of media synchronization (mediasync), gathering contributions from the most representative and influential experts. Understanding the challenges of this field in the current multi-sensory, multi-device, and multi-protocol world is not an easy task. The book revisits the foundations of mediasync, including theoretical frameworks and models, highlights ongoing research efforts, like hybrid broadband broadcast (HBB) delivery and users' perception modeling (i.e., Quality of Experience or QoE), and paves the way for the future (e.g., towards the deployment of multi-sensory and ultra-realistic experiences). Although many advances around mediasync have been devised and deployed, this area of research is getting renewed attention to overcome remaining challenges in the next-generation (heterogeneous and ubiquitous) media ecosystem. Given the significant advances in this research area, its current relevance and the multiple disciplines it involves, the availability of a reference book on mediasync becomes necessary. This book fills the gap in this context. In particular, it addresses key aspects and reviews the most relevant contributions within the mediasync research space, from different perspectives. Mediasync: Handbook on Multimedia Synchronization is the perfect companion for scholars and practitioners that want to acquire strong knowledge about this research area, and also approach the challenges behind ensuring the best mediated experiences, by providing the adequate synchronization between the media elements that constitute these experiences

    Using microtasks to crowdsource DBpedia entity classification: A study in workflow design

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    DBpedia is at the core of the Linked Open Data Cloud and widely used in research and applications. However, it is far from being perfect. Its content suffers from many flaws, as a result of factual errors inherited from Wikipedia or incomplete mappings from Wikipedia infobox to DBpedia ontology. In this work we focus on one class of such problems, un-typed entities. We propose a hierarchical tree-based approach to categorize DBpedia entities according to the DBpedia ontology using human computation and paid microtasks. We analyse the main dimensions of the crowdsourcing exercise in depth in order to come up with suggestions for workflow design and study three different workflows with automatic and hybrid prediction mechanisms to select possible candidates for the most specific category from the DBpedia ontology. To test our approach, we run experiments on CrowdFlower using a gold standard dataset of 120 previously unclassified entities. In our studies human-computation driven approaches generally achieved higher precision at lower cost when compared to workflows with automatic predictors. However, each of the tested workflows has its merit and none of them seems to perform exceptionally well on the entities that the DBpedia Extraction Framework fails to classify. We discuss these findings and their potential implications for the design of effective crowdsourced entity classification in DBpedia and beyond

    Quality of Service Controlled Multimedia Transport Protocol

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    PhDThis research looks at the design of an open transport protocol that supports a range of services including multimedia over low data-rate networks. Low data-rate multimedia applications require a system that provides quality of service (QoS) assurance and flexibility. One promising field is the area of content-based coding. Content-based systems use an array of protocols to select the optimum set of coding algorithms. A content-based transport protocol integrates a content-based application to a transmission network. General transport protocols form a bottleneck in low data-rate multimedia communicationbsy limiting throughpuot r by not maintainingt iming requirementsT. his work presents an original model of a transport protocol that eliminates the bottleneck by introducing a flexible yet efficient algorithm that uses an open approach to flexibility and holistic architectureto promoteQ oS.T he flexibility andt ransparenccyo mesi n the form of a fixed syntaxt hat providesa seto f transportp rotocols emanticsT. he mediaQ oSi s maintained by defining a generic descriptor. Overall, the structure of the protocol is based on a single adaptablea lgorithm that supportsa pplication independencen, etwork independencea nd quality of service. The transportp rotocol was evaluatedth rougha set of assessmentos:f f-line; off-line for a specific application; and on-line for a specific application. Application contexts used MPEG-4 test material where the on-line assessmenuts eda modified MPEG-4 pl; yer. The performanceo f the QoSc ontrolledt ransportp rotocoli s often bettert hano thers chemews hen appropriateQ oS controlledm anagemenatl gorithmsa re selectedT. his is shownf irst for an off-line assessmenwt here the performancei s compared between the QoS controlled multiplexer,a n emulatedM PEG-4F lexMux multiplexers chemea, ndt he targetr equirements. The performanceis also shownt o be better in a real environmentw hen the QoS controlled multiplexeri s comparedw ith the real MPEG-4F lexMux scheme

    Multimedia tools for the creation of online learning materials : a critique

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    D1.1 DEMAND ASSESSMENT FRAMEWORK

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    This report proposes the initial draft of the LeADS ADS Framework composed by three major elements; identification and definition of technologies in scope; skills included under those technologies, and definition of job roles, where other skills frameworks are considered for comparison and alignment. The report summarises the first workshop held by the project with external constituencies even though the feedback will be incorporated in the final version of the framework, where the layer of job roles will be completed, and the others revised according to additional input. This framework serves as reference for the next step in LeADS: the assessment of the demand and the supply
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