296,895 research outputs found

    A Model for Semantic IS Standards

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    We argue that, in order to suggest improvements of any kind to semantic information system (IS) standards, better understanding of the conceptual structure of semantic IS standard is required. This study develops a model for semantic IS standard, based on literature and expert knowledge. The model is validated by case descriptions of two particular semantic IS standards. The model shows characteristics of semantic IS standards. Some of these characteristics might become steering factors for improving the development, adoption and quality of standards, among others

    Morphological Cues for Lexical Semantics

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    Most natural language processing tasks require lexical semantic information. Automated acquisition of this information would thus increase the robustness and portability of NLP systems. This paper describes an acquisition method which makes use of fixed correspondences between derivational affixes and lexical semantic information. One advantage of this method, and of other methods that rely only on surface characteristics of language, is that the necessary input is currently available

    Optimized mobile thin clients through a MPEG-4 BiFS semantic remote display framework

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    According to the thin client computing principle, the user interface is physically separated from the application logic. In practice only a viewer component is executed on the client device, rendering the display updates received from the distant application server and capturing the user interaction. Existing remote display frameworks are not optimized to encode the complex scenes of modern applications, which are composed of objects with very diverse graphical characteristics. In order to tackle this challenge, we propose to transfer to the client, in addition to the binary encoded objects, semantic information about the characteristics of each object. Through this semantic knowledge, the client is enabled to react autonomously on user input and does not have to wait for the display update from the server. Resulting in a reduction of the interaction latency and a mitigation of the bursty remote display traffic pattern, the presented framework is of particular interest in a wireless context, where the bandwidth is limited and expensive. In this paper, we describe a generic architecture of a semantic remote display framework. Furthermore, we have developed a prototype using the MPEG-4 Binary Format for Scenes to convey the semantic information to the client. We experimentally compare the bandwidth consumption of MPEG-4 BiFS with existing, non-semantic, remote display frameworks. In a text editing scenario, we realize an average reduction of 23% of the data peaks that are observed in remote display protocol traffic

    Features for Killer Apps from a Semantic Web Perspective

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    There are certain features that that distinguish killer apps from other ordinary applications. This chapter examines those features in the context of the semantic web, in the hope that a better understanding of the characteristics of killer apps might encourage their consideration when developing semantic web applications. Killer apps are highly tranformative technologies that create new e-commerce venues and widespread patterns of behaviour. Information technology, generally, and the Web, in particular, have benefited from killer apps to create new networks of users and increase its value. The semantic web community on the other hand is still awaiting a killer app that proves the superiority of its technologies. The authors hope that this chapter will help to highlight some of the common ingredients of killer apps in e-commerce, and discuss how such applications might emerge in the semantic web

    Use of implicit graph for recommending relevant videos: a simulated evaluation

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    In this paper, we propose a model for exploiting community based usage information for video retrieval. Implicit usage information from a pool of past users could be a valuable source to address the difficulties caused due to the semantic gap problem. We propose a graph-based implicit feedback model in which all the usage information can be represented. A number of recommendation algorithms were suggested and experimented. A simulated user evaluation is conducted on the TREC VID collection and the results are presented. Analyzing the results we found some common characteristics on the best performing algorithms, which could indicate the best way of exploiting this type of usage information
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