Titlebook: Knowledge and Systems Sciences; 18th International S Jian Chen,Thanaruk Theeramunkong,Xijin Tang Conference proceedings 2017 Springer Natur

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Comparative Study of Using Word Co-occurrence to Extract Disease Symptoms from Web Documents, phrases to extract disease symptom explanations from downloaded hospital documents. The research results are applied to construct the semantic relations between disease-topic names and symptom explanations for enhancing the automatic problem-solving system. The machine learning technique, Support V

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Forecasting the Duration of Network Public Opinions Caused by the Failure of Public Policies: The Cgly to propose a model that could predict the duration before the release of policies, in order to provide some rational suggestions to decision makers to reduce the risk of publishing public policies. This paper argues that these factors involve four dimensions: audience, environment, reality, and

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Modeling of Interdependent Critical Infrastructures Network in Consideration of the Hierarchy,system. This paper proposes a model of interdependent critical infrastructures network in consideration of the hierarchy. Physical interdependence among critical infrastructures is taken into consideration. Even more specifically, the interdependent network is constructed by analyzing the energy, wa

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Emergency Attribute Significance Ranking Method Based on Information Gain,e of attributes. Firstly, it builds the emergency decision table based on rough set theory. Secondly, it uses information gain to measure the objective significance of emergency attributes. Further, the information gain is combined with the prior knowledge of experts to rank the total significance o

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Predicting Hashtag Popularity of Social Emergency by a Robust Feature Extraction Method,prediction for social emergencies is more and more practical for E-governance. How to predict the hashtag popularity for social emergency has become a considerably important task. However, previous research mainly focused on commercial hashtag prediction, such as marketing and promotion. For the has

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The Distribution Semantics of Extended Argumentation,ndard abstract argumentation framework. In this paper, we define the distribution semantics for extended argumentation frameworks, and moreover derive inference procedures from existing proof procedures of such extended argumentation frameworks. While doing so we focus on extended argumentation fram