Abstract In this paper, we design an access control system that enables a specific user to use a document in a Hangul document system. The system structure designed in this paper is to analyze the Hangul document structure and modify the Hangul document head information. By modifying the function of a specific field of Hangul document head information, a user who does not have data on the transformed... In this paper, we design an access control system that enables a specific user to use a document in a Hangul document system. The system structure designed in this paper is to analyze the Hangul document structure and modify the Hangul document head information. By modifying the function of a specific field of Hangul document head information, a user who does not have data on the transformed information will not be able to open and view the document. In this way, it can control the access to important Hangul documents. In this paper, we actually implemented what we design and performed experiments. Experimental results show that the access control system operates normally. Read More Read Less

Abstract TJSchema is a framework for the management of temporal documents stored in JSON format in a NoSQL database, similar to the Ï„XSchema framework proposed for XML. In this work, we extend TSchema to temporal schema versioning support. The proposed approach provides a systematic solution to the challenging task of evolving a JSON schema while maintaining all schema versions with their corresponding instances and, thus, guarantees the bookkeeping of... TJSchema is a framework for the management of temporal documents stored in JSON format in a NoSQL database, similar to the Ï„XSchema framework proposed for XML. In this work, we extend TSchema to temporal schema versioning support. The proposed approach provides a systematic solution to the challenging task of evolving a JSON schema while maintaining all schema versions with their corresponding instances and, thus, guarantees the bookkeeping of a full history of both data and schemas. All components of a temporal JSON schema (i.e., conventional schema, temporal logical and physical characteristics) are allowed to vary over time to reflect changes in the real world and, thus, in application requirements. To this end, four sets of primitives for changing JSON schema components and their related JSON instance documents are introduced. The feasibility of our approach and the usage of the proposed primitives have been shown through a detailed and illustrative example. Read More Read Less

Abstract Network centralities are amongst the most important measures for tracking and locating crucial nodes in a network. In this paper, we propose a general approach for identifying the most suitable centrality measure for detecting key concepts in a semantic or linguistic network. We experiment with seven network centrality measures (degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, current-flow betweenness centrality, current-flow closeness centrality and communicability centrality). For the purpose... Network centralities are amongst the most important measures for tracking and locating crucial nodes in a network. In this paper, we propose a general approach for identifying the most suitable centrality measure for detecting key concepts in a semantic or linguistic network. We experiment with seven network centrality measures (degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, current-flow betweenness centrality, current-flow closeness centrality and communicability centrality). For the purpose of evaluation, we compare the original Wikipedia hyperlink network with a constructed concept network. The obtained results indicate that all seven used measures have good potential for identifying key terms, and that degree centrality achieves the best score. A good score is also obtained for current-flow betweenness centrality and current-flow closeness centrality. Read More Read Less

Abstract With the explosive growth of the mass data, the traditional architecture of the information system has been difficult to deal with enterprise needs. Data mining has become an important means of business innovation; it changed the development direction of cloud computing and also lead software-as-a-service (SaaS) becomes the main indicator of the era of cloud 2.0. This paper proposed an improved K-means algorithm, and uses it to... With the explosive growth of the mass data, the traditional architecture of the information system has been difficult to deal with enterprise needs. Data mining has become an important means of business innovation; it changed the development direction of cloud computing and also lead software-as-a-service (SaaS) becomes the main indicator of the era of cloud 2.0. This paper proposed an improved K-means algorithm, and uses it to evaluate interactive mechanism of airline industry ecosystem stability. Aiming at the clustering instability problem of traditional K-means algorithm in the process of random selection, this paper proposes a stochastic selection method for clustering centers initialization, the efficiency of the algorithm also has been greatly improved. By using data mining method, we make analysis of the ecological stability system of aviation industry; the result shows that technological innovation is the source of system stability, so it is the key link to the stability of the industrial ecosystem. Read More Read Less

Abstract Metaphor is a result of emotion conceptualization hidden in human language. Due to the complexity and abstraction of human emotion, it is difficult to calculate and create a model for it. However, emotion modeling and calculation is of great significance in the process of machine translation (MT). Usually, incorporating the calculation of emotion metaphors in machine translation could make the language much more vivid and meet the standards... Metaphor is a result of emotion conceptualization hidden in human language. Due to the complexity and abstraction of human emotion, it is difficult to calculate and create a model for it. However, emotion modeling and calculation is of great significance in the process of machine translation (MT). Usually, incorporating the calculation of emotion metaphors in machine translation could make the language much more vivid and meet the standards of faithfulness, expressiveness and elegance in translation. Normally, calculation of emotion metaphor adopts machine learning and pattern identification, and it requires the samples from emotion metaphor corpus of large scale and high quality. The thesis builds an English and Chinese bilingual corpus with affluent emotion metaphors and supports data to emotion metaphor calculation by machine translation. In the process of building emotion metaphor corpus, 5 main procedures including theoretical framework, design principles, data collection, data annotation and index monitoring are illustrated. Finally, machine translation experiment has been done in emotion metaphor corpus built in this thesis, which adopts same recurrent neural network and LSTM mnemon to compare with existing machine translation corpora. Result shows that the emotion metaphor corpus built in this thesis is able to express emotion metaphor in machine translation. Read More Read Less