If we view data as a set of queries with an answer, what would a model be? In this paper we explore this question. The motivation is that there are more and more kinds of data that have to be analysed. data of such a ...
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Big data is both a curse and a blessing. A blessing because the unprecedented amount of detailed data allows for research in, e.g., social sciences and health on scales that were until recently unimaginable. A curse, ...
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In recent years a variety of mining algorithms, to derive all frequent subtrees from a database of labeled ordered rooted trees has been developed. These algorithms share properties such as enumeration strategies and ...
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In recent years a variety of mining algorithms, to derive all frequent subtrees from a database of labeled ordered rooted trees has been developed. These algorithms share properties such as enumeration strategies and pruning techniques. They differ however in the tree inclusion relation used and the way attribute values are dealt with. In this work we investigate the different approaches with respect to 'usefulness' of the derived patterns, in particular, the performance of classifiers that use the derived patterns as features. In order to find a good trade-off between expressiveness and runtime performance of the different approaches, we also take the complexity of the different classifiers into account, as well as the run time and memory usage of the different approaches. The experiments are performed on two real data sets, and two synthetic data sets. The results show that significant improvement in both predictive performance and computational efficiency can be gained by choosing the right tree mining approach.
Large data is challenging for most existing discovery algorithms, for several reasons. First of all, such data leads to enormous hypothesis spaces, making exhaustive search infeasible. Second, many variants of essenti...
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The energy Internet (EI) presents a novel paradigm for renewable energy distribution that utilizes communication and computing technologies to revolutionize the conventional intelligent transportation systems (ITSs) a...
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The objective of Advanced Persistent Threat (APT) attacks is to exploit Cyber-Physical Systems (CPSs) in combination with the Industrial Internet of Things (I-IoT) by using fast attack methods. Machine learning (ML) t...
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Introduction: The Industrial Internet of Things (IIoT) is a technology that connects devices to collect data and conduct in-depth analysis to provide value-added services to industries. The integration of the physical...
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