Results 281 to 290 of about 829,286 (307)
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Investigative Graph Search using Graph Databases
2019 First International Conference on Graph Computing (GC), 2019Identification and tracking of individuals or groups perpetrating latent or emergent behaviors are significant in home-land security, cyber security, behavioral health, and consumer analytics. Graphs provide an effective formal mechanism to capture the relationships among individuals of interest as well as their behavior patterns.
Shashika R. Muramudalige +3 more
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Crowdstore: A Crowdsourcing Graph Database
2016Existing crowdsourcing database systems fail to support complex, collaborative or responsive crowd work. These systems implement human computation as independent tasks published online, and subsequently chosen by individual workers. Such pull model does not support worker collaboration and its expertise matching relies on workers’ subjective self ...
Liptchinsky, Vitaliy +3 more
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Proceedings of the 32nd ACM SIGMOD-SIGACT-SIGAI symposium on Principles of database systems, 2013
Graph databases have gained renewed interest in the last years, due to its applications in areas such as the Semantic Web and Social Networks Analysis. We study the problem of querying graph databases, and, in particular, the expressiveness and complexity of evaluation for several general-purpose query languages, such as the regular path queries and ...
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Graph databases have gained renewed interest in the last years, due to its applications in areas such as the Semantic Web and Social Networks Analysis. We study the problem of querying graph databases, and, in particular, the expressiveness and complexity of evaluation for several general-purpose query languages, such as the regular path queries and ...
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Evolving Database Conceptual Graph Partitioning
2016Algorithms of graph partitioning exploited in conceptual database design were reused to define a methodology of database concept preservation. An algorithm, the concept construction algorithm that relates concept theory to computer science was designed. This algorithm, however, is not suitable for implementation.
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Graph Databases and Graph Neural Networks
Journal of Integrated Information ManagementPurpose - Nowadays, social networks, online media sharing and e-commerce platforms generate a vast amount of data, which, among other information, capture the interactions among the users. Storing, analyzing and exploiting the aforementioned information allow the exploration of hidden and unstructured patterns.
Tsolakidis, Stratos +4 more
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GRAPHED: A Graph Description Diagram for Graph Databases
2018Within recent years, graph database systems have become very popular and deployed mainly in situations where the relationship between data is significant, such as in social networks. Although they do not require a particular schema design, a data model contributes to their consistency.
Gustavo Van Erven +3 more
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NO SQL Database: Graph database
Egyptian Journal of Artificial Intelligence, 2022openaire +1 more source
Modal Schema Graphs for Graph Databases
2019Although graph databases are conceived schema-less, additional knowledge about the data’s structure and/or semantics is beneficial in many graph database management tasks, from efficient storage, over query optimization, up to data integration. Today’s commonly used graph data models do not represent primal suspects regarding their lack of schema prior
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