Global ETD Search
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Showing 1 to 18 of 18 for “"graph databases"”.
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Design Foundations of Graph Databases
The property graph model and graph database management systems such as Neo4j have become increasingly popular. Naturally, questions around graph data modelling best practices arise. Graph databases are perceived as very intuitive and our research will provide evidence to showcase their benefits. …
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A natural language interface for querying graph databases
… amount of knowledge in the world is stored in graph databases. However, most people have limited or no understanding of database schemes and query languages. Providing a tool that translates natural language queries into structured queries allows people without this technical knowledge or …
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Efficient processing of advanced structural queries in graph databases
Recent decades witnessed a rapid proliferation of graph data, such as chemical structures and business processes. Structural queries are frequently issued in these domains, and hence, attract extensive attention. Due to data inconsistency and noise, a recent trend is to study similarity queries. …
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Privacy, Access Control, and Integrity for Large Graph Databases
Graph data are extensively utilized in social networks, collaboration networks, geo-social networks, and communication networks. Their growing usage in cyberspaces poses daunting security and privacy challenges. Data publication requires privacy-protection mechanisms to guard against information …
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G-hash: Towards Fast Kernel-based Similarity Search in Large Graph Databases
Structured data such as graphs and networks have posed significant challenges to fundamental aspects of data management including efficient storage, indexing, and similarity search. With the fast accumulation of graph databases, similarity search in graph databases has emerged as an important …
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A BIM - GIS Integrated Information Model Using Semantic Web and RDF Graph Databases
… as Building Information Modelling (BIM) and Geographical Information Systems (GIS) are frequently used to meet such high demands. However, sharing data and information between these two domains is still challenging. At the same time, the semantic or syntactic strategies for inter-communication …
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Schema-Driven Exceptional Query Generation for Soccer Analytics using Relational and Graph Databases
… exceptional queries using relational and graph databases. A schema-driven framework loading soccer data on a weekly basis was introduced using the Statsbomb open-source dataset. This framework automatically generates thousands of queries, executes them efficiently, and retrieves relevant …
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Mogway: um arcabouço para bancos de dados múltiplos grafos
Graphs are a powerful representation technique, capable of capturing the relationship between entities. They are useful to understand a wide variety of data sets from many areas like science, government and business. In the last years has resurged the interest in storing and managing graph data due …
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Storage and processing systems for power-law graphs
Large graphs abound around us - online social networks, Web graphs, the Internet, citation networks, protein interaction networks, telephone call graphs, peer-to-peer overlay networks, electric power grid networks, etc. Many real- life graphs are power-law graphs. A fundamental challenge in today’s …
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Enabling access to and exploration of information graphs
… access to and exploration of rich information graphs. Within businesses, organizations, and among researchers, data is produced in many forms, large volumes, and different contexts. As a consequence of this heterogeneity, many applications find more useful modelling their datasets with the …
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Multi-modal and inertial sensor solutions for navigation-type factor graphs
… refactorization of the nonparametric factor graph, and asymptotically approximates the underlying Chapman-Kolmogorov equations. Our method tracks dominant modes in the marginal posteriors of all variables with minimal approximation error, while suppressing almost all lowlikelihood modes (in a …
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Generic Architecture for Predictive Computational Modelling with Application to Financial Data Analysis: Integration of Semantic Approach and Machine Learning
… data mining based on a semantic approach, graph-based methods (ontology, knowledge graphs, graph databases) and advanced machine learning methods. The main focus of my research is data pre-processing aimed at a more efficient selection of input features to the computational model. Since the …
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PPDQ-BG: Parallel Partition and Distributed Query Processing for Big Graphs
… requires expensive computations to perform big graph analysis and query processing. Graph data represent irregular and unstructured relationships that usually result in a lack of locality so that it is often difficult to extract relevant information from big graphs. Although there have been …
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HPC-based Parallel Algorithms for Generating Random Networks and Some Other Network Analysis Problems
… systems including multi-core, distributed, and graphics processor units (GPU) based systems. In this dissertation, we present distributed memory parallel algorithms for generating massive random networks and a novel GPU-based algorithm for index searching. This dissertation is divided into two …
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Interoperability between the StraboSpot graph database and GIS software– A Malpais Mesa Use Case
Geographic Information Systems (GIS) have been used by field geoscientists for decades to digitally collect data with several benefits: observations can be made in the field at a map independent scale while using multiple basemaps, the burdensome task of digitizing handwritten field notes and maps …
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Graph based management of temporal data
… and retrieval of temporal data using an existing graph database system (i.e., Neo4j) without extending with additional operators. Our work focuses on temporal data represented as intervals (event with a start and end time). We propose a novel way of storing temporal interval as cartesian points …
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A Framework for Semantic Enterprise Transformations
… and applies these patterns to an underlying graph structure. By generalizing semantic transformations through patterns and graphs (Chapter 5), it is possible not only to determine a traversal path to find a corresponding code value, but to predict missing nodes through the use of graph …
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Modelling of Functions and Malfunctions in Industrial Processes: An Applied Ontology Approach
… renown to be flexible (e.g., by using knowledge graphs), both these facts help with I2. Finally, technologies associated with applied ontology (such as knowledge-graph databases, automated reasoning, logic-based modelling, etc) possess various techniques for storing and retrieving information …