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About 10,000 papers for “graph data structures”

Graph Applications to Data Structures

V. Manjula · Advanced materials research · 2012

This paper presents a topic on Graph theory and its application to data Structures which I consider basic and useful to students in APPLIED MATHEMATICS and ENGINEERING.This paper gives an elementary introduction of Graph theory and its application to data structures. Elements of Graph theory are indispensable in almost all computer Science areas .It can be used in Some areas such as syntactic analysis, fault detection, diagnosis in computers and minimal path problems. The computer representation and manipulation of graph are also discussed so that certain algorithms can be included .A major theme of this paper is to study Graph theory and its Application to data structures Furthermore I hope the students not only learn the course but also develop their analogy perceive, formulate and to solve mathematical programs Thus Graphs especially trees, binary trees are used widely in the representation of data structures this course one can develop mathematical maturity, ability to understand and create mathematical argumentsMethod of derivation is procedure given in the text books with necessary formulae and their application . Concepts and notations from discrete mathematics are useful in studying and describing objects and problems in branches of computer science, such as computer algorithms, programming languages.

Cited by 0

VISUALIZING GRAPH DATA STRUCTURES: ENHANCING UNDERSTANDING IN DATA STRUCTURES EDUCATION

В. А. Колесников · Transactions of Kremenchuk Mykhailo Ostrohradskyi National University · 2024

Graph data structures constitute fundamental components within computer science, serving as versatile models for representing interconnected relationships in a myriad of domains, including social networks, transportation systems, and biological networks.However, comprehending the intricacies inherent to graphs often poses a significant challenge for students enrolled in data structures courses.This paper endeavors to explore the transformative potential of visualization techniques in bolstering comprehension and engagement within the realm of graph data structures education.Drawing upon insights gleaned from cognitive psychology and educational research, we embark on an examination of how visualization methodologies can serve as catalysts for fostering deeper understanding and retention of abstract concepts, thereby elevating overall learning outcomes.Through literature review, we meticulously scrutinize a number of studies, each illuminating the efficacy of graph visualization tools in enhancing student comprehension and problem-solving skills.Moreover, we ardently advocate for the adoption of an active learning paradigm, wherein students are not merely passive recipients of knowledge but are actively encouraged to develop their visualization applications.Such an approach not only nurtures creativity and innovation, but also engenders a profound appreciation for the intricate nuances inherent to graph representations.Additionally, we delve into the underlying principles and methodologies of graph visualization, offering a discourse on techniques for crafting visually compelling graph layouts.By synthesizing a rich tapestry of research findings and practical insights, this paper endeavors to furnish educators with some strategies for seamlessly integrating visualization techniques into the fabric of data structures curricula.Ultimately, our overarching objective is to empower students to navigate the labyrinthine complexities of graph data structures with unwavering confidence, consummate proficiency, and reverence for the elegance imbued within graphical representations.

Cited by 0Open access

Using Graph Data Structures for Event Logs

Stefan Esser · Data Archiving and Networked Services (DANS) · 2019

This report is the result of a Capita Selecta research project conducted at Eindhoven University of Technology. The objective of the project was to explore how event log data can be stored in and queried from labeled prooperty graphs used in graph databases.

Cited by 5Open access

Object-oriented description of graph data structures

Alexey Demakov · Programming and Computer Software · 2007

A solution method for problems of processing graph data structures is presented. This method is based on the use of the specialized language TreeDL and on its extendable compiler. The capabilities of the language and of the compiler exceed the existing solutions, which makes the proposed method more efficient than its analogs.

Cited by 1

Temporal Pattern Recognition in Graph Data Structures

Pietro Daverio, Hassan Nazeer Chaudhry, Alessandro Margara et al. · 2021 IEEE International Conference on Big Data (Big Data) · 2021

Graph data structures model relations between entities in various domains. Graph processing systems enable scalable distributed computations over large graphs, but are limited to static scenarios in which the structure of the graph does not change. However, many applications are dynamic in nature, and this reflects to graphs that continuously evolve over time. In these contexts, understanding the evolution of graphs is key to enable timely reactions when necessary. We address this problem by proposing a new model to express temporal patterns over graph data structures. The model seamlessly integrates computations over graphs to extract relevant values, and temporal operators that define patterns of interest in the evolution of the graph. We present the syntax and semantics of our model and discuss its concrete implementation in FlowGraph, a middleware for temporal pattern recognition in large scale graphs. FlowGraph presents a level of performance that is comparable to state-of-the-art graph processing tools when processing static graphs. In the presence of temporal patterns, it can further optimize processing by avoiding complex graph computations until strictly necessary for pattern evaluation.

Cited by 6

A graph theoretic model of data structures

ACM SIGIR Forum · 1972

The widespread development of large shared data bases has proceeded mainly on empirical notions. Only in the past few years have there been attempts at formalizing the underlying concepts into a theory of data structures. The present models have been founded on the well-established mathematical theories of sets, relations and graphs, but few descriptions have been sufficiently developed to meet the needs of a complete theory of data structures. The set theoretic formalism offered by Childs(1) or Schwartz(2) or the relational model by Codd(3) are useful but fail to give a complete description of the complex structures found in modern data bases. The graph theoretic concepts found in papers by Harary and Hsiao(4) and Earley(5) are more appealing but need further elaboration. This paper is an attempt to develop a graph theoretic model into a useful formalism for describing and manipulating data structures.

Cited by 3

Data Structures and their Planar Graph Layouts

Christopher Auer, Christian Bachmaier, Franz J. Brandenburg et al. · Journal of Graph Algorithms and Applications · 2018

In a stack layout, also known as book embedding, the vertices of a graph are placed on a line and an edge is a data item that is pushed on the stack at the left vertex and removed at the right vertex. The LIFO principle of the stack is represented by a rainbow of nesting edges. We introduce linear cylindric drawings for the representation of the working principles of fundamental data structures including stack, queue, double-stack and deque. The resulting graphs are called stack (queue, double-stack, deque) graphs. We characterize the feasibility of a sequence of insertions and removals by planarity and use the graph classes to compare the relative power of these data structures. In particular, we show that the deque graphs are the linear cylindric planar graphs and are the subgraphs of the planar graphs with a Hamiltonian path. In comparison, the double-stack graphs are the graphs with a linear layout in the plane and are known as the subgraphs of the planar graphs with a Hamiltonian cycle. Hence, the power of the queue mode of a deque is expressed both by the differences between Hamiltonian path and Hamiltonian cycle and by linear layouts on the cylinder and in the plane. It is also reflected in the dual graph. Linear cylindric drawings provide an intuitive planar representation of the FIFO principle of a queue. We show that a queue graph augmented by a Hamiltonian path has a dual of the same type and that the dual has an Eulerian path. Finally, we study recognition problems.

Cited by 7Open access

Towards Interactive Design of Graph Data Structures

Sha, Rachna · Digital Access to Scholarship at Harvard (DASH) (Harvard University) · 2021

Graph Frameworks and Databases are critical components of modern software. The need to analyze massive graph datasets have spurred the development of Graph Systems. Graph Frameworks and Libraries with tuned Graph data structures are continuously being developed to handle new workloads and data patterns. This presents a need for a Graph system that has knowledge of its design space and is capable of combining fundamental design constructs to generate optimal graph data structures for a given hardware, data pattern and workload. We propose leveraging non-graph systems with these capabilities and with an overlap in its design space with Graph systems, to bring this intelligence to Graph Systems. As a first step in this process, we have implemented a Key-Value Graph Generator, that demonstrates the use of key-value approach in designing Adjacency List and Compressed Sparse Row (CSR). Our hypothesis is that if we can successfully model Graph data structures using key-value approach then we can leverage learned key-value system and create an interactive and automatic Graph system.

Cited by 0

orbweaver: Fast and Efficient Graph Data Structures

Andres Quintero · 2023

Seamlessly build and manipulate graph structures, leveraging its high-performance methods for filtering, joining, and mutating data. Ensures that mutations and changes to the graph are performed in place, streamlining your workflow for optimal productivity.

Cited by 0Open access

Designing Fast Graph Data Structures: An Experimental Approach

John R. Black, Jr., Charles U. Martel · 1998

We show that simple alternatives to standard graph representations can substantially improve performance. We obtained these results by conducting an experimental study of the performance of basic data structures for storing lists of values. We then used these results to design and evaluate fast implementations of Breadth-First-Search (BFS) and Depth-First-Search (DFS). Using our improved data structures can improve performance of BFS and DFS by a factor of 20 or more over a standard representation. Our main focus is on understanding and quantifying architectural effects on algorithm performance. The most important aspect is improving data locality since the penalty for cache misses is becoming a significant overhead for modern machines. For the basic data structures we show that array-based lists are much faster than basic linked list implementations for sequential access (sometimes by a factor of 10 or more). We also suggest a simple enhancement to the linked list which improves pe...

Cited by 0

Effective Visualization of Data Structures in Graph Databases

Adam Dudáš · Journal of Image and Graphics · 2024

To efficiently store data where the relationships between individual objects are essential, the use of a graph database model is recommended. After storing the data, it is necessary to further analyze it using statistical methods or visualize it within the context of exploratory data analysis. Such visualization is crucial for understanding the structure and content of the database. However, commonly used visualization tools often fall short in terms of interactivity and effectiveness. The main objective of the presented work is the design and implementation of a novel model for the visualization of data structures stored in graph databases with the use of two natural graphical models—the standard topological layout of the database and the so-called clustered layout of a graph database. The presented graphical models are focused on interactive visualization, mainly scaling of visualization and development of database objects, and principles of effective visualization. Implementation of the proposed approach was evaluated via case studies on three model graph databases of various sizes—Messaging database (16 objects, 16 relationships), Library database (16 objects, 32 relationships) and Movie database (171 objects, 253 relationships). Compared to the standard Neo4j tool for the visual representation of property graphs in graph databases, the proposed model presents improvement in terms of the number of visualization models, effectivity of the visualization, and development of objects in the visualized database.

Cited by 3Open access

Data structures and computation graph of murefi models.

Laura Marie Helleckes (12206910), Michael Osthege (12206913), Wolfgang Wiechert (39471) et al. · Figshare · 2022

<p>Elements in a comprehensive parameter vector are mapped to replicate-wise model instances. In the depicted example, the model instances for both replicates “B1” and “B2” share <i>θ</i><sub>1,global</sub> as the first element in their parameter vectors. The second model parameter <i>θ</i><sub>2</sub> is local to the replicates, hence the full parameter vector (left) is comprised of three elements. Model predictions are made such that they resemble the structure of the observed data, having the same number of time points for each predicted time series. An objective function calculating the sum of log-likelihoods is created by associating predicted and observed time series via their respective calibration models. By associating the calibration models based on the dependent variable name, a calibration model may be re-used across multiple replicates, or kept local if, for example, the observations were obtained by different methods.</p>

Cited by 0Open access

Generating Graphical Editors for Graph-like Data Structures

Technische Universität München, Gerwin Klein, Technische Universität München et al. · 1999

Generating Graphical Editors for Graph-like Data Structures Many modern applications favor one or more graphical diagram editors, of which – despite their different look & feel and problem domains – on a closer look many have very similar functionality. Examples are UML class diagrams, finite automata, electronic circuit diagrams, or network charts. Their similarity is, that in an abstract way they all work on, edit and display a graph. These editors and diagram viewers are mostly implemented by hand. Although this work is not very often done from scratch but rather with the help of some object oriented framework, it remains a complex task with usually high development costs. This diploma thesis focuses on how the development and maintenance cost for this kind of graphical editors can be reduced. The problem is addressed in three steps: We analyze example applications, extracting and structuring classes of requirements for graph editors to examine and clearly define the problem domain. We develop a description language that allows to define and fully specify a graph editor

Cited by 0