Wyniki wyszukiwania dla: GRAPH DATABASES - MOST Wiedzy

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Wyniki wyszukiwania dla: GRAPH DATABASES

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Wyniki wyszukiwania dla: GRAPH DATABASES

  • EvOLAP Graph – Evolution and OLAP-Aware Graph Data Model

    Publikacja

    - Rok 2018

    The 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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  • The complexity of bicriteria tree-depth

    Publikacja

    The 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

    Computer 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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  • Graph Representation Integrating Signals for Emotion Recognition and Analysis

    Data 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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