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Titlebook: Database and Expert Systems Applications; 30th International C Sven Hartmann,Josef Küng,Ismail Khalil Conference proceedings 2019 Springer

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COMET: A Contextualized Molecule-Based Matching Techniquey matching represents a building-block for these tasks. However, existing approaches only consider inter-schema mapping of data sources, and are not able to manage several contexts during entity matching. We devise COMET, an entity matching technique that relies on both the knowledge stated in RDF v
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Differentially Private Non-parametric Machine Learning as a Servicemachine learning models requires the release of the parameters of the model, releasing non-parametric machine learning models requires the release of the training dataset along with the parameters. The release of the training dataset creates a risk of breach of privacy. An alternative to the release
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Jonah Pears,Laura Bocchi,Andy Kingetc.) are generated and processed every day. Row pattern matching for the sequence data stored in relational databases was standardized as SQL/RPR in 2016. Today, in addition to relational databases, there are many frameworks for processing a large amount of data in parallel and distributed computin
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Implementing IT in Production Settingsem. Furthermore, in the context of high-dimensional datasets, adhering to strict privacy legislation can be projected to a W[2]-complete problem whereby all privacy violating attribute combinations must be identified. While traditional anonymisation algorithms incur high levels of information loss w
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The ‘New’ Versus The ‘Old’ Economy Debate are some limitations of Role-Based Access Control (RBAC) in HBase. The coarse-grained access permissions produce little effect in many cases, and the elements used for authorization are not comprehensive enough. Attribute-Based Access Control (ABAC) is suitable for the authorization of NoSQL data s
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Some Observations on Recent Growth Theoryions. People often use system logs for anomaly detection. However, manually inspecting system logs to detect anomaly is unfeasible due to the increasing scale and complexity of distributed systems. As a result, various methods of automatically mining log patterns for anomaly detection have been deve
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Gerard H. Kuper,Elmer Sterken,Els Westery aims at finding an anomaly subsequence in a time-series. Time-series is essentially dynamic, so monitoring the discord of a streaming time-series is an important problem. This paper addresses this problem and proposes SDM (Streaming Discord Monitoring), an algorithm that efficiently updates the di
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