Personalized recommender systems are commonly used to filter information in social media, and recommendations are derived by training machine learning algorithms on these data. It is thus important to understand how m...
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In recent years extracting relevant information from biomedical and clinical texts such as research articles, discharge summaries, or electronic health records have been a subject of many research efforts and shared c...
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With the rapid development of Internet of Things(IoT)technologies,the detection and analysis of malware have become a matter of concern in the industrial application of Cyber-Physical System(CPS)that provides various ...
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With the rapid development of Internet of Things(IoT)technologies,the detection and analysis of malware have become a matter of concern in the industrial application of Cyber-Physical System(CPS)that provides various services using the IoT ***,many advanced machine learning methods such as deep learning are popular in the research of malware detection and analysis,and some achievements have been made so ***,there are also some *** example,considering the noise and outliers in the existing datasets of malware,some methods are not robust ***,the accuracy of malware classification still needs to be *** at this issue,we propose a novel method that combines the correntropy and the deep learning *** our proposed method for malware detection and analysis,given the success of the mixture correntropy as an effective similarity measure in addressing complex datasets with noise,it is therefore incorporated into a popular deep learning model,i.e.,Convolutional Neural Network(CNN),to reconstruct its loss function,with the purpose of further detecting the features of *** present the detailed design process of our ***,the proposed method is tested both on a real-world malware dataset and a popular benchmark dataset to verify its learning performance.
New application domains ranging from the area of computational science (e.g. CERN Datagrid) to international business processes (e.g. Wal-Mart logistics) demand ever increasing storage capacities on a global scale. Th...
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Measuring semantic relatedness plays an important role in information retrieval and Natural Language Processing. However, little attention has been paid to measuring semantic relatedness between named entities, which ...
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This study aims to build live texturing augmented reality to enhance the attractiveness of coloring books. This research has four main stages, namely data gathering, object preparations, software development and evalu...
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Automatic evaluation systems in the field of automatic summarization have been relying on the availability of gold standard summaries for over ten years. Gold standard summaries are expensive to obtain and often requi...
In recent years, the ongoing adoption of Semantic Web technologies has lead to a large amount of Linked Data that has been generated. While in the early days of the Semantic Web we were fighting data scarcity, nowaday...
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We present a new approach to enriching under-specified representations of content to be realized as text. Our approach uses an attribute grammar to propagate missing information where needed in a tree that represents ...
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