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Wyniki wyszukiwania dla: graph databases
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EvOLAP Graph – Evolution and OLAP-Aware Graph Data Model
PublikacjaThe objective of this paper is to propose a graph model that would be suitable for providing OLAP features on graph databases. The included features allow for a multidimensional and multilevel view on data and support analytical queries on operational and historical graph data. In contrast to many existing approaches tailored for static graphs, the paper addresses the issue for the changing graph schema. The model, named Evolution...
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Nonrelational Databases DE 2023_2024
Kursy OnlineThis course discusses three types of non-relational databases (i.e., document, graph, and key-value). The course is aimed at students in the 5th semester of data engineering.
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Non-relational Databases 2022/2023
Kursy OnlineThis course discusses the three types of non-relational databases (i.e. document, graph, key-value). The course is aimed at students in the 7th semester of computer science.
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Non-relational Databases 2023/2024
Kursy OnlineThis course discusses the three types of non-relational databases (i.e. document, graph, key-value). The course is aimed at students in the 7th semester of computer science.
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Nonrelational Databases DE 2022_2023
Kursy OnlineWithin this course the four types of non-relational databases (i.e. document, graph, key-value and column-oriented) are discussed. The course is aimed at students of the 5th semester of data engineering.
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The complexity of bicriteria tree-depth
PublikacjaThe tree-depth problem can be seen as finding an elimination tree of minimum height for a given input graph G. We introduce a bicriteria generalization in which additionally the width of the elimination tree needs to be bounded by some input integer b. We are interested in the case when G is the line graph of a tree, proving that the problem is NP-hard and obtaining a polynomial-time additive 2b-approximation algorithm. This particular...
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Combining Road Network Data from OpenStreetMap with an Authoritative Database
PublikacjaComputer modeling of road networks requires detailed and up-to-date dataset. This paper proposes a method of combining authoritative databases with OpenStreetMap (OSM) system. The complete route is established by finding paths in the graph constructed from partial data obtained from OSM. In order to correlate data from both sources, a method of coordinate conversion is proposed. The algorithm queries road data from OSM and provides...
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Joanna Raczek dr inż.
OsobyWykształcenie 1997 -- 2001 Studia inżynierskie, Wydział Fizyki Technicznej i Matematyki Stosowanej, Politechnika Gdańska. Kierunek: Matematyka, specjalność: Matematyka Stosowana. 2001 -- 2003 Studia magisterskie, Wydział Fizyki Technicznej i Matematyki Stosowanej, Politechnika Gdańska. Kierunek: Matematyka, specjalność: Matematyka Stosowana. 2000 -- 2004 Studia inżynierskie, Wydział Elektroniki, Informatyki i Telekomunikacji,...
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Krzysztof Goczyła prof. dr hab. inż.
OsobyKrzysztof Goczyła, profesor zwyczajny Politechniki Gdańskiej, informatyk, specjalista z inżynierii oprogramowania, inżynierii wiedzy i baz danych. Ukończył studia wyższe na Wydziale Elektroniki Politechniki Gdańskiej w 1976 r. jako magister inżynier elektronik w specjalności automatyka. Na Politechnice Gdańskiej pracuje od 1976. Na Wydziale Elektroniki PG w 1982 r. uzyskał doktorat z informatyki, a w 1999 r. habilitację. W 2012...
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Graph Representation Integrating Signals for Emotion Recognition and Analysis
PublikacjaData reusability is an important feature of current research, just in every field of science. Modern research in Affective Computing, often rely on datasets containing experiments-originated data such as biosignals, video clips, or images. Moreover, conducting experiments with a vast number of participants to build datasets for Affective Computing research is time-consuming and expensive. Therefore, it is extremely important to...
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Łukasz Szeremeta
OsobyMoje obecne obszary badawcze to zagadnienia związane z grafami własności, cheminformatyką i Semantic Web. Interesuję się również najnowszymi zastosowaniami sztucznej inteligencji.