2,192 research outputs found

    Adaptive hypermedia for education and training

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    Adaptive hypermedia (AH) is an alternative to the traditional, one-size-fits-all approach in the development of hypermedia systems. AH systems build a model of the goals, preferences, and knowledge of each individual user; this model is used throughout the interaction with the user to adapt to the needs of that particular user (Brusilovsky, 1996b). For example, a student in an adaptive educational hypermedia system will be given a presentation that is adapted specifically to his or her knowledge of the subject (De Bra & Calvi, 1998; Hothi, Hall, & Sly, 2000) as well as a suggested set of the most relevant links to proceed further (Brusilovsky, Eklund, & Schwarz, 1998; Kavcic, 2004). An adaptive electronic encyclopedia will personalize the content of an article to augment the user's existing knowledge and interests (Bontcheva & Wilks, 2005; Milosavljevic, 1997). A museum guide will adapt the presentation about every visited object to the user's individual path through the museum (Oberlander et al., 1998; Stock et al., 2007). Adaptive hypermedia belongs to the class of user-adaptive systems (Schneider-Hufschmidt, KĂĽhme, & Malinowski, 1993). A distinctive feature of an adaptive system is an explicit user model that represents user knowledge, goals, and interests, as well as other features that enable the system to adapt to different users with their own specific set of goals. An adaptive system collects data for the user model from various sources that can include implicitly observing user interaction and explicitly requesting direct input from the user. The user model is applied to provide an adaptation effect, that is, tailor interaction to different users in the same context. In different kinds of adaptive systems, adaptation effects could vary greatly. In AH systems, it is limited to three major adaptation technologies: adaptive content selection, adaptive navigation support, and adaptive presentation. The first of these three technologies comes from the fields of adaptive information retrieval (IR) and intelligent tutoring systems (ITS). When the user searches for information, the system adaptively selects and prioritizes the most relevant items (Brajnik, Guida, & Tasso, 1987; Brusilovsky, 1992b)

    Automation and hypermedia technology applications

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    This paper represents a progress report on HyLite (Hypermedia Library technology): a research and development activity to produce a versatile system as part of NASA's technology thrusts in automation, information sciences, and communications. HyLite can be used as a system or tool to facilitate the creation and maintenance of large distributed electronic libraries. The contents of such a library may be software components, hardware parts or designs, scientific data sets or databases, configuration management information, etc. Proliferation of computer use has made the diversity and quantity of information too large for any single user to sort, process, and utilize effectively. In response to this information deluge, we have created HyLite to enable the user to process relevant information into a more efficient organization for presentation, retrieval, and readability. To accomplish this end, we have incorporated various AI techniques into the HyLite hypermedia engine to facilitate parameters and properties of the system. The proposed techniques include intelligent searching tools for the libraries, intelligent retrievals, and navigational assistance based on user histories. HyLite itself is based on an earlier project, the Encyclopedia of Software Components (ESC) which used hypermedia to facilitate and encourage software reuse

    Understanding user experience of mobile video: Framework, measurement, and optimization

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    Since users have become the focus of product/service design in last decade, the term User eXperience (UX) has been frequently used in the field of Human-Computer-Interaction (HCI). Research on UX facilitates a better understanding of the various aspects of the user’s interaction with the product or service. Mobile video, as a new and promising service and research field, has attracted great attention. Due to the significance of UX in the success of mobile video (Jordan, 2002), many researchers have centered on this area, examining users’ expectations, motivations, requirements, and usage context. As a result, many influencing factors have been explored (Buchinger, Kriglstein, Brandt & Hlavacs, 2011; Buchinger, Kriglstein & Hlavacs, 2009). However, a general framework for specific mobile video service is lacking for structuring such a great number of factors. To measure user experience of multimedia services such as mobile video, quality of experience (QoE) has recently become a prominent concept. In contrast to the traditionally used concept quality of service (QoS), QoE not only involves objectively measuring the delivered service but also takes into account user’s needs and desires when using the service, emphasizing the user’s overall acceptability on the service. Many QoE metrics are able to estimate the user perceived quality or acceptability of mobile video, but may be not enough accurate for the overall UX prediction due to the complexity of UX. Only a few frameworks of QoE have addressed more aspects of UX for mobile multimedia applications but need be transformed into practical measures. The challenge of optimizing UX remains adaptations to the resource constrains (e.g., network conditions, mobile device capabilities, and heterogeneous usage contexts) as well as meeting complicated user requirements (e.g., usage purposes and personal preferences). In this chapter, we investigate the existing important UX frameworks, compare their similarities and discuss some important features that fit in the mobile video service. Based on the previous research, we propose a simple UX framework for mobile video application by mapping a variety of influencing factors of UX upon a typical mobile video delivery system. Each component and its factors are explored with comprehensive literature reviews. The proposed framework may benefit in user-centred design of mobile video through taking a complete consideration of UX influences and in improvement of mobile videoservice quality by adjusting the values of certain factors to produce a positive user experience. It may also facilitate relative research in the way of locating important issues to study, clarifying research scopes, and setting up proper study procedures. We then review a great deal of research on UX measurement, including QoE metrics and QoE frameworks of mobile multimedia. Finally, we discuss how to achieve an optimal quality of user experience by focusing on the issues of various aspects of UX of mobile video. In the conclusion, we suggest some open issues for future study

    Telematics programme (1991-1994). EUR 15402 EN

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    Distributed multimedia systems

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    A distributed multimedia system (DMS) is an integrated communication, computing, and information system that enables the processing, management, delivery, and presentation of synchronized multimedia information with quality-of-service guarantees. Multimedia information may include discrete media data, such as text, data, and images, and continuous media data, such as video and audio. Such a system enhances human communications by exploiting both visual and aural senses and provides the ultimate flexibility in work and entertainment, allowing one to collaborate with remote participants, view movies on demand, access on-line digital libraries from the desktop, and so forth. In this paper, we present a technical survey of a DMS. We give an overview of distributed multimedia systems, examine the fundamental concept of digital media, identify the applications, and survey the important enabling technologies.published_or_final_versio

    Automatic document classification and extraction system (ADoCES)

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    Document processing is a critical element of office automation. Document image processing begins from the Optical Character Recognition (OCR) phase with complex processing for document classification and extraction. Document classification is a process that classifies an incoming document into a particular predefined document type. Document extraction is a process that extracts information pertinent to the users from the content of a document and assigns the information as the values of the “logical structure” of the document type. Therefore, after document classification and extraction, a paper document will be represented in its digital form instead of its original image file format, which is called a frame instance. A frame instance is an operable and efficient form that can be processed and manipulated during document filing and retrieval. This dissertation describes a system to support a complete procedure, which begins with the scanning of the paper document into the system and ends with the output of an effective digital form of the original document. This is a general-purpose system with “learning” ability and, therefore, it can be adapted easily to many application domains. In this dissertation, the “logical closeness” segmentation method is proposed. A novel representation of document layout structure - Labeled Directed Weighted Graph (LDWG) and a methodology of transforming document segmentation into LDWG representation are described. To find a match between two LDWGs, string representation matching is applied first instead of doing graph comparison directly, which reduces the time necessary to make the comparison. Applying artificial intelligence, the system is able to learn from experiences and build samples of LDWGs to represent each document type. In addition, the concept of frame templates is used for the document logical structure representation. The concept of Document Type Hierarchy (DTH) is also enhanced to express the hierarchical relation over the logical structures existing among the documents

    The Post-2015 Global Agenda: A Framework for Country Diagnostics

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    With the 2015 deadline for the current Millennium Development Goals (MDGs) drawing near, the global community is shaping a new set of international development goals for the longer term. The process has involved consultations led by the UN Open Working Group guided by the 2013 report, "A New Global Partnership" of the UN High-level Panel. The work so far indicates that the post-2015 development agenda will encompass goals for social, economic, and environmental sustainability with broader coverage than the current MDGs. This paper refers to these post-2015 development goals as Sustainable Development Goals, or SDGs.The World Bank Group is developing a diagnostic framework to assess the implications of implementing the post-2015 global development agenda at the country level. This framework has been applied to a pilot case study on Uganda, and some of the results of this study are highlighted here for illustrative purposes. The WBG has also developed a multi-country database that provides a starting point for similar diagnostics in other countries. Subject to data availability, the framework may be used to analyze likely progress in SDGs and their determinants and to discuss policy and financing options to accelerate their progress. This work has been shared with the Intergovernmental Committee of Experts on Sustainable Development Financing.The purpose of this paper is to demonstrate the application of this framework, drawing on the pilot study of Uganda
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