Browsing by Subject "Graph databases"

Now showing 1 - 3 of 3

Open Access
Efficient querying of SBGN maps stored in a graph database
(2019-02) Karaca, Mustafa Enes
Graph visualization is an important research area that endeavors to make graphs more understandable and easier to analyze. In various domains, graph visualization techniques and standards are developed to effectively analyze underlying graph based data. Systems Biology Graphical Notation (SBGN) is a standard language for modeling biological processes and pathways through graph visualization. Information about SBGN maps can be stored in XML based SBGNML files. libSBGN is a Java/C++ library for reading, writing SBGN-ML and manipulating SBGN maps in an object-oriented manner. Graph databases store data in terms of a graph structure consisting nodes and their relationships. Performing a computation on graph data stored in a graph database by traversals is more e cient than accessing tabled data in relational databases through costly join operations. Neo4j is a prominent graph database that provides a proprietary language named Cypher for querying stored graph data. Neo4j allows writing user defined procedures in Java as plugins to improve capabilities of Neo4j with third party Java libraries. With this thesis, we enable modeling SBGN maps in Neo4j graph database with support for compound structures. Using this SBGN data model in Neo4j, we developed graph based user defined procedures in Java using libSBGN as a plugin to Neo4j. These procedures were used to implement graph query algorithms, such as neighborhood, common stream, and paths between, along with helper functions such as populating a database from an SBGN map and loading an SBGN map from a graph database. These user defined procedures are designed to produce or consume SBGN-ML; hence, they can be used by any visualization tool which can import/export SBGN-ML text. Newt, a web based editor for viewing and diting SBGN maps, is such a tool making use of these procedures and hosting a local Neo4j instance by providing a web service to execute Cypher statements.
Open Access
Generating time-varying road network data using sparse trajectories
(IEEE, 2016-12) Eser, Elif; Kocayusufoğlu, F.; Eravci, Bahaedd; Ferhatosmanoglu, Hakan; Larriba-Pey, J. L.
While research on time-varying graphs has attracted recent attention, the research community has limited or no access to real datasets to develop effective algorithms and systems. Using noisy and sparse GPS traces from vehicles, we develop a time-varying road network data set where edge weights differ over time. We present our methodology and share this dataset, along with a graph manipulation tool. We estimate the traffic conditions using the sparse GPS data available by characterizing the sparsity issues and assessing the properties of travel sequence data frequency domain. We develop interpolation methods to complete the sparse data into a complete graph dataset with realistic time-varying edge values. We evaluate the performance of time-varying and static shortest path solutions over the generated dynamic road network. The shortest paths using the dynamic graph produce very different results than the static version. We provide an independent Java API and a graph database to analyze and manipulate the generated time-varying graph data easily, not requiring any knowledge about the inners of the graph database system. We expect our solution to support researchers to pursue problems of time-varying graphs in terms of theoretical, algorithmic, and systems aspects. The data and Java API are available at: http://elif.eser.bilkent.edu.tr/roadnetwork. © 2016 IEEE.
Open Access
Hydra: Detecting fraud in financial transactions via graph based representation and visual analysis
(IEEE, 2020) Canbaz, Yusuf Sait; Doğrusöz, Uğur; Çeliksoy, M.; Güngör, F.; Kurban, K.
In this paper, we describe a web based tool named Hydra for analyzing financial transaction data with the aim to detect or verify fraudulent activities via visual analysis and graph based querying. Hydra exclusively uses graph based query algorithms to mine useful information in the transaction database, presents the results visually, facilitating interactive graphical analysis with state-of-the-art graph visualization technologies. We present the various components of Hydra and their aims. In addition, a number of different types of scenarios using these components for a network of prepaid card transactions are provided to illustrate the use of Hydra for detecting or verifying fraudulent activities.