140 research outputs found

    PicShark: mitigating metadata scarcity through large-scale P2P collaboration

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    With the commoditization of digital devices, personal information and media sharing is becoming a key application on the pervasive Web. In such a context, data annotation rather than data production is the main bottleneck. Metadata scarcity represents a major obstacle preventing efficient information processing in large and heterogeneous communities. However, social communities also open the door to new possibilities for addressing local metadata scarcity by taking advantage of global collections of resources. We propose to tackle the lack of metadata in large-scale distributed systems through a collaborative process leveraging on both content and metadata. We develop a community-based and self-organizing system called PicShark in which information entropy—in terms of missing metadata—is gradually alleviated through decentralized instance and schema matching. Our approach focuses on semi-structured metadata and confines computationally expensive operations to the edge of the network, while keeping distributed operations as simple as possible to ensure scalability. PicShark builds on structured Peer-to-Peer networks for distributed look-up operations, but extends the application of self-organization principles to the propagation of metadata and the creation of schema mappings. We demonstrate the practical applicability of our method in an image sharing scenario and provide experimental evidences illustrating the validity of our approac

    Study on Open Financing Models of Small and Medium-Sized Internet Education Enterprises

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    Small and medium-sized Internet education enterprises have faced financing difficulties and expensive financing due to their small size, low assets and lack of collateral. The development of the Internet, big data and sharing economy provides new ideas for small and medium-sized Internet education enterprises to alleviate financing difficulties. This paper combines the traditional financing model with the internet financing model to construct an open financing model for small and medium-sized internet education enterprises, which has the characteristics of multi-subject participation, openness, high efficiency, omni-directionality, resource integration, etc., and is able to effectively solve the information asymmetry, reduce the financing risk, and improve the efficiency of financing faced in the financing process. The conclusion of the study provides a reference for solving the financing constraints of small and medium-sized Internet education enterprises, which is conducive to promoting the growth of small and medium-sized Internet education enterprises

    Distributed First Order Logic

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    Distributed First Order Logic (DFOL) has been introduced more than ten years ago with the purpose of formalising distributed knowledge-based systems, where knowledge about heterogeneous domains is scattered into a set of interconnected modules. DFOL formalises the knowledge contained in each module by means of first-order theories, and the interconnections between modules by means of special inference rules called bridge rules. Despite their restricted form in the original DFOL formulation, bridge rules have influenced several works in the areas of heterogeneous knowledge integration, modular knowledge representation, and schema/ontology matching. This, in turn, has fostered extensions and modifications of the original DFOL that have never been systematically described and published. This paper tackles the lack of a comprehensive description of DFOL by providing a systematic account of a completely revised and extended version of the logic, together with a sound and complete axiomatisation of a general form of bridge rules based on Natural Deduction. The resulting DFOL framework is then proposed as a clear formal tool for the representation of and reasoning about distributed knowledge and bridge rules

    Developing Web Services Using Workflow Model: An Inter-organizational Perspective

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    This paper discusses how a workflow model can be used in the design and development of web services composition. We particularly investigate the development of web services composition in an inter-organizational workflow environment. We discuss respectively how to design an inter-organizational workflow from scratch when there is no existing internal workflow, and how to make existing internal workflows work together in an inter-organizational workflow environment

    PicShark: Mitigating Metadata Scarcity Through Large-Scale P2P Collaboration

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    Abstract With the commoditization of digital devices, personal information and media sharing is becoming a key application on the pervasive Web. In such a context, data annotation rather than data production is the main bottleneck. Metadata scarcity represents a major obstacle preventing effcient information processing in large and heterogeneous communities. However, social communities also open the door to new possibilities for addressing local metadata scarcity by taking advantage of global collections of resources. We propose to tackle the lack of metadata in large-scale distributed systems through a collaborative process leveraging on both content and metadata. We develop a community-based and self-organizing system called PicShark in which information entropy in terms of missing metadata is gradually alleviated through decentralized instance and schema matching. Our approach focuses on semi- structured metadata and confines computationally expensive operations to the edge of the network, while keeping distributed operations as simple as possible to ensure scalability. PicShark builds on structured Peer-to-Peer networks for distributed look-up operations, but extends the application of self-organization principles to the propagation of metadata and the creation of schema mappings. We demonstrate the practical applicability of our method in an image sharing scenario and provide experimental evidences illustrating the validity of our approach

    LightChain: A DHT-based Blockchain for Resource Constrained Environments

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    As an append-only distributed database, blockchain is utilized in a vast variety of applications including the cryptocurrency and Internet-of-Things (IoT). The existing blockchain solutions have downsides in communication and storage efficiency, convergence to centralization, and consistency problems. In this paper, we propose LightChain, which is the first blockchain architecture that operates over a Distributed Hash Table (DHT) of participating peers. LightChain is a permissionless blockchain that provides addressable blocks and transactions within the network, which makes them efficiently accessible by all the peers. Each block and transaction is replicated within the DHT of peers and is retrieved in an on-demand manner. Hence, peers in LightChain are not required to retrieve or keep the entire blockchain. LightChain is fair as all of the participating peers have a uniform chance of being involved in the consensus regardless of their influence such as hashing power or stake. LightChain provides a deterministic fork-resolving strategy as well as a blacklisting mechanism, and it is secure against colluding adversarial peers attacking the availability and integrity of the system. We provide mathematical analysis and experimental results on scenarios involving 10K nodes to demonstrate the security and fairness of LightChain. As we experimentally show in this paper, compared to the mainstream blockchains like Bitcoin and Ethereum, LightChain requires around 66 times less per node storage, and is around 380 times faster on bootstrapping a new node to the system, while each LightChain node is rewarded equally likely for participating in the protocol

    A Comparison of Mobile Payment Procedures in Finnish and Chinese Markets

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    Researchers are particularly interested in factors that affect the adoption, innovations and diffusion of mobile payment, which is a typical and wide application of ICTS (Information Communication Technology Services) in developed and developing countries. Though mobile payment is an exciting domain and rapidly evolved in recent years, the existence of standardized, interconnected and widely-accepted mobile payment procedures is crucial for successful diffusion of mobile payment and has mobile commerce globally, even in one country or region. In this paper we make a comparison of mobile payment procedures in the Finnish and the Chinese market. Current payment procedures can be categorized by using strategic, participatory and operational criteria, according to the morphological method. Based on these, we analyze the current contraints on the mobile payment procedures in the Finnish-Chinese market in order to make it clear whether we can develop a generally accepted mobile payment integrative solution or merge different procedures into an interoperability system via interconnected participants with high-level protocols and regulation when necessary, because different market participants may have separate benefits

    A framework for information integration using ontological foundations

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    With the increasing amount of data, ability to integrate information has always been a competitive advantage in information management. Semantic heterogeneity reconciliation is an important challenge of many information interoperability applications such as data exchange and data integration. In spite of a large amount of research in this area, the lack of theoretical foundations behind semantic heterogeneity reconciliation techniques has resulted in many ad-hoc approaches. In this thesis, I address this issue by providing ontological foundations for semantic heterogeneity reconciliation in information integration. In particular, I investigate fundamental semantic relations between properties from an ontological point of view and show how one of the basic and natural relations between properties – inferring implicit properties from existing properties – can be used to enhance information integration. These ontological foundations have been exploited in four aspects of information integration. First, I propose novel algorithms for semantic enrichment of schema mappings. Second, using correspondences between similar properties at different levels of abstraction, I propose a configurable data integration system, in which query rewriting techniques allows the tradeoff between accuracy and completeness in query answering. Third, to keep the semantics in data exchange, I propose an entity preserving data exchange approach that reflects source entities in the target independent of classification of entities. Finally, to improve the efficiency of the data exchange approach proposed in this thesis, I propose an extended model of the column-store model called sliced column store. Working prototypes of the techniques proposed in this thesis are implemented to show the feasibility of realizing these techniques. Experiments that have been performed using various datasets show the techniques proposed in this thesis outperform many existing techniques in terms of ability to handle semantic heterogeneities and performance of information exchange
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