Relevant bibliographies by topics / Connection graph

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Connection graph'

Author: Grafiati
Published: 25 May 2024

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Journal articles on the topic "Connection graph"

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Ismail, Sumarno, Isran K. Hasan, Tesya Sigar, and Salmun K. Nasib. "RAINBOW CONNECTION NUMBER AND TOTAL RAINBOW CONNECTION NUMBER OF AMALGAMATION RESULTS DIAMOND GRAPH(〖Br〗_4) AND FAN GRAPH(F_3)." BAREKENG: Jurnal Ilmu Matematika dan Terapan 16, no. 1 (March 21, 2022): 023–30. http://dx.doi.org/10.30598/barekengvol16iss1pp023-030.

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If be a graph and edge coloring of G is a function , rainbow connection number is the minimum-k coloration of the rainbow on the edge of graph G and denoted by rc(G). Rainbow connection numbers can be applied to the result of operations on some special graphs, such as diamond graphs and fan graphs. Graph operation is a method used to obtain a new graph by combining two graphs. This study performed amalgamation operations to obtain rainbow connection numbers and rainbow-total-connection numbers in diamond graphs ( ) and fan graphs ( ) or . Based on the research, it is obtained that the rainbow-connection number theorem on the amalgamation result of the diamond graph ( ) and fan graph ( is with . Furthermore, the theorem related to the total rainbow-connection number on the amalgamation result of the diamond graph( ) and the fan graph ( is obtained, namely with .
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Bustan, A. W., A. N. M. Salman, and P. E. Putri. "On the locating rainbow connection number of amalgamation of complete graphs." Journal of Physics: Conference Series 2543, no. 1 (July 1, 2023): 012004. http://dx.doi.org/10.1088/1742-6596/2543/1/012004.

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Abstract Locating rainbow connection number determines the minimum number of colors connecting any two vertices of a graph with a rainbow vertex path and also verifies that the given colors produce a different rainbow code for each vertex. Locating rainbow connection number of graphs is a new mathematical concept, especially in graph theory, which combines the concepts of the rainbow vertex coloring and the partition dimension. In this paper, we determine the locating rainbow connection number of amalgamation of complete graphs.
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Alrowaili, Dalal Awadh, Faiz Farid, and Muhammad Javaid. "Gutman Connection Index of Graphs under Operations." Symmetry 15, no. 1 (December 22, 2022): 21. http://dx.doi.org/10.3390/sym15010021.

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In the modern era, mathematical modeling consisting of graph theoretic parameters or invariants applied to solve the problems existing in various disciplines of physical sciences like computer sciences, physics, and chemistry. Topological indices (TIs) are one of the graph invariants which are frequently used to identify the different physicochemical and structural properties of molecular graphs. Wiener index is the first distance-based TI that is used to compute the boiling points of the paraffine. For a graph F, the recently developed Gutman Connection (GC) index is defined on all the unordered pairs of vertices as the sum of the multiplications of the connection numbers and the distance between them. In this note, the GC index of the operation-based symmetric networks called by first derived graph D1(F) (subdivision graph), second derived graph D2(F) (vertex-semitotal graph), third derived graph D3(F) (edge-semitotal graph) and fourth derived graph D4(F) (total graph) are computed in their general expressions consisting of various TIs of the parent graph F, where these operation-based symmetric graphs are obtained by applying the operations of subdivision, vertex semitotal, edge semitotal and the total on the graph F respectively.
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ZHANG, YINGYING, and XIAOYU ZHU. "Proper Vertex Connection and Graph Operations." Journal of Interconnection Networks 19, no. 02 (June 2019): 1950001. http://dx.doi.org/10.1142/s0219265919500014.

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A path in a vertex-colored graph is a vertex-proper path if any two internal adjacent vertices differ in color. A vertex-colored graph is proper vertex k-connected if any two vertices of the graph are connected by k disjoint vertex-proper paths of the graph. For a k-connected graph G, the proper vertex k-connection number of G, denoted by pvck(G), is defined as the smallest number of colors required to make G proper vertex k-connected. A vertex-colored graph is strong proper vertex-connected, if for any two vertices u, v of the graph, there exists a vertex-proper u-v geodesic. For a connected graph G, the strong proper vertex-connection number of G, denoted by spvc(G), is the smallest number of colors required to make G strong proper vertex-connected. In this paper, we study the proper vertex k-connection number and the strong proper vertex-connection number on the join of two graphs, the Cartesian, lexicographic, strong and direct product, and present exact values or upper bounds for these operations of graphs. Then we apply these results to some instances of Cartesian and lexicographic product networks.
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Farid, Faiz, Muhammad Javaid, and Ebenezer Bonyah. "Computing Connection Distance Index of Derived Graphs." Mathematical Problems in Engineering 2022 (July 18, 2022): 1–15. http://dx.doi.org/10.1155/2022/1439177.

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Distance based topological indices (TIs) play a vital role in the study of various structural and chemical aspects for the molecular graphs. The first distance-based TI is used to find the boiling point of paraffin. The connection distance (CD) index is a latest developed TI that is defined as the sum of all the products of distances between pair of vertices with the sum of their respective connection numbers . In this paper, we computed CD indices of the different derived graphs (subdivision graph S G , vertex-semitotal graph R G , edge-semitotal graph Q G and total graph T G obtained from the graph G under various operations of subdivision in the form of degree distance (DD) and CD indices of the basic graphs including some other algebraic expressions.
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Javaid, Muhammad, Muhammad Khubab Siddique, and Ebenezer Bonyah. "Computing Gutman Connection Index of Thorn Graphs." Journal of Mathematics 2021 (November 15, 2021): 1–13. http://dx.doi.org/10.1155/2021/2289514.

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Chemical structural formula can be represented by chemical graphs in which atoms are considered as vertices and bonds between them are considered as edges. A topological index is a real value that is numerically obtained from a chemical graph to predict its various physical and chemical properties. Thorn graphs are obtained by attaching pendant vertices to the different vertices of a graph under certain conditions. In this paper, a numerical relation between the Gutman connection (GC) index of a graph and its thorn graph is established. Moreover, the obtained result is also illustrated by computing the GC index for the particular families of the thorn graphs such as thorn paths, thorn rods, thorn stars, and thorn rings.
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Lihawa, Indrawati, Sumarno Ismail, Isran K. Hasan, Lailany Yahya, Salmun K. Nasib, and Nisky Imansyah Yahya. "Bilangan Terhubung Titik Pelangi pada Graf Hasil Operasi Korona Graf Prisma (P_(m,2)) dan Graf Lintasan (P_3)." Jambura Journal of Mathematics 4, no. 1 (January 1, 2022): 145–51. http://dx.doi.org/10.34312/jjom.v4i1.11826.

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Rainbow vertex-connection number is the minimum k-coloring on the vertex graph G and is denoted by rvc(G). Besides, the rainbow-vertex connection number can be applied to some special graphs, such as prism graph and path graph. Graph operation is a method used to create a new graph by combining two graphs. Therefore, this research uses corona product operation to form rainbow-vertex connection number at the graph resulting from corona product operation of prism graph and path graph (Pm,2 P3) (P3 Pm,2). The results of this study obtain that the theorem of rainbow vertex-connection number at the graph resulting from corona product operation of prism graph and path graph (Pm,2 P3) (P3 Pm,2) for 3 = m = 7 are rvc (G) = 2m rvc (G) = 2.
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Yahya, Nisky Imansyah, Ainun Fatmawati, Nurwan Nurwan, and Salmun K. Nasib. "RAINBOW VERTEX-CONNECTION NUMBER ON COMB PRODUCT OPERATION OF CYCLE GRAPH (C_4) AND COMPLETE BIPARTITE GRAPH (K_(3,N))." BAREKENG: Jurnal Ilmu Matematika dan Terapan 17, no. 2 (June 11, 2023): 0673–84. http://dx.doi.org/10.30598/barekengvol17iss2pp0673-0684.

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Rainbow vertex-connection number is the minimum colors assignment to the vertices of the graph, such that each vertex is connected by a path whose edges have distinct colors and is denoted by . The rainbow vertex connection number can be applied to graphs resulting from operations. One of the methods to create a new graph is to perform operations between two graphs. Thus, this research uses comb product operation to determine rainbow-vertex connection number resulting from comb product operation of cycle graph and complete bipartite graph & . The research finding obtains the theorem of rainbow vertex-connection number at the graph of for while the theorem of rainbow vertex-connection number at the graph of for for .
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Asif, Muhammad, Bartłomiej Kizielewicz, Atiq ur Rehman, Muhammad Hussain, and Wojciech Sałabun. "Study of θϕ Networks via Zagreb Connection Indices." Symmetry 13, no. 11 (October 21, 2021): 1991. http://dx.doi.org/10.3390/sym13111991.

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Graph theory can be used to optimize interconnection network systems. The compatibility of such networks mainly depends on their topology. Topological indices may characterize the topology of such networks. In this work, we studied a symmetric network θϕ formed by ϕ time repetition of the process of joining θ copies of a selected graph Ω in such a way that corresponding vertices of Ω in all the copies are joined with each other by a new edge. The symmetry of θϕ is ensured by the involvement of complete graph Kθ in the construction process. The free hand to choose an initial graph Ω and formation of chemical graphs using θϕΩ enhance its importance as a family of graphs which covers all the pre-defined graphs, along with space for new graphs, possibly formed in this way. We used Zagreb connection indices for the characterization of θϕΩ. These indices have gained worth in the field of chemical graph theory in very small duration due to their predictive power for enthalpy, entropy, and acentric factor. These computations are mathematically novel and assist in topological characterization of θϕΩ to enable its emerging use.
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Ma, Yingbin, and Kairui Nie. "Rainbow Vertex Connection Numbers and Total Rainbow Connection Numbers of Middle and Total Graphs." Ars Combinatoria 157 (December 31, 2023): 45–52. http://dx.doi.org/10.61091/ars157-04.

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A vertex-colouring of a graph Γ is rainbow vertex connected if every pair of vertices ( u , v ) in Γ there is a u − v path whose internal vertices have different colours. The rainbow vertex connection number of a graph Γ , is the minimum number of colours needed to make Γ rainbow vertex connected, denoted by r v c ( Γ ) . Here, we study the rainbow vertex connection numbers of middle and total graphs. A total-colouring of a graph Γ is total rainbow connected if every pair of vertices ( u , v ) in Γ there is a u − v path whose edges and internal vertices have different colours. The total rainbow connection number of Γ , is the minimum number of colours required to colour the edges and vertices of Γ in order to make Γ total rainbow connected, denoted by t r c ( Γ ) . In this paper, we also research the total rainbow connection numbers of middle and total graphs.
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Dissertations / Theses on the topic "Connection graph"

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Sato, Cristiane Maria. "Homomorfismos de grafos." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-07082008-105246/.

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Homomorfismos de grafos são funções do conjunto de vértices de um grafo no conjunto de vértices de outro grafo que preservam adjacências. O estudo de homomorfismos de grafos é bastante abrangente, existindo muitas linhas de pesquisa sobre esse tópico. Nesta dissertação, apresentaremos resultados sobre homomorfismos de grafos relacionados a pseudo-aleatoriedade, convergência de seqüência de grafos e matrizes de conexão de invariantes de grafos. Esta linha tem se mostrado muito rica, não apenas pelos seus resultados, como também pelas técnicas utilizadas nas demonstrações. Em especial, destacamos a diversidade das ferramentas matemáticas que são usadas, que incluem resultados clássicos de álgebra, probabilidade e análise.
Graph homomorphisms are functions from the vertex set of a graph to the vertex set of another graph that preserve adjacencies. The study of graph homomorphisms is very broad, and there are several lines of research about this topic. In this dissertation, we present results about graph homomorphisms related to convergence of graph sequences and connection matrices of graph parameters. This line of research has been proved to be very rich, not only for its results, but also for the proof techniques. In particular, we highlight the diversity of mathematical tools used, including classical results from Algebra, Probability and Analysis.
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Berg, Deborah. "Connections Between Voting Theory and Graph Theory." Scholarship @ Claremont, 2005. https://scholarship.claremont.edu/hmc_theses/178.

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Mathematical concepts have aided the progression of many different fields of study. Math is not only helpful in science and engineering, but also in the humanities and social sciences. Therefore, it seemed quite natural to apply my preliminary work with set intersections to voting theory, and that application has helped to focus my thesis. Rather than studying set intersections in general, I am attempting to study set intersections and what they mean in a voting situation. This can lead to better ways to model preferences and to predict which campaign platforms will be most popular. Because I feel that allowing people to only vote for one candidate results in a loss of too much information, I consider approval voting, where people can vote for as many platforms as they like.
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Zini, Roger. "Placement, routage conjoints et hierarchiques de reseaux prediffuses." Paris 6, 1987. http://www.theses.fr/1987PA066116.

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Cette these propose un algorithme original de construction hierarchique d'arbres de steiner ainsi qu'une technique d'estimation de longueur au fur et a mesure de cette construction. Deux algorithmes de partitionnement d'hypergraphes, de maniere gloutonne ou par recuit simule sans rejets, y sont exposes. Elle introduit enfin un concept de directions d'attraction permettant d'effectuer un placement routage de circuits vlsi, a implanter sur des reseaux prediffuses, sous forme de systeme regule par retroaction entre le placement, le routage et l'analyse temporelle, afin d'obtenir du circuit, par un placement-routage adequat, les performances temporelles souhaitees
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Mirza, Batul J. "Jumping Connections: A Graph-Theoretic Model for Recommender Systems." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/31370.

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Recommender systems have become paramount to customize information access and reduce information overload. They serve multiple uses, ranging from suggesting products and artifacts (to consumers), to bringing people together by the connections induced by (similar) reactions to products and services. This thesis presents a graph-theoretic model that casts recommendation as a process of 'jumping connections' in a graph. In addition to emphasizing the social network aspect, this viewpoint provides a novel evaluation criterion for recommender systems. Algorithms for recommender systems are distinguished not in terms of predicted ratings of services/artifacts, but in terms of the combinations of people and artifacts that they bring together. We present an algorithmic framework drawn from random graph theory and outline an analysis for one particular form of jump called a 'hammock.' Experimental results on two datasets collected over the Internet demonstrate the validity of this approach.
Master of Science
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Chaudhuri, Sanjay. "Using the structure of d-connecting paths as a qualitative measure of the strength of dependence /." Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/8948.

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Candel, Gaëlle. "Connecting graphs to machine learning." Electronic Thesis or Diss., Université Paris sciences et lettres, 2022. http://www.theses.fr/2022UPSLE018.

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L’objet de cette thèse est de proposer des approches nouvelles permettant l’utilisation d’algorithmes d’apprentissage automatique travaillant usuellement des données tabulaires aux graphes. Un graphe est une structure de donnée composée de nœuds reliés entre eux par des liens. Cette structure peut être représentée sous la forme d’une matrice, où chaque connexion entre de nœuds est représentée par une valeur non nulle, permettant une manipulation des données plus facile. Néanmoins, par leurs différences structurelles, la transposition d’un algorithme exploitant des données tabulaires aux graphes ne donne pas les résultats escomptés. Deux caractéristiques rendent cette adaptation difficile : la faible connectivité des nœuds ainsi que la distribution en loi de puissance du degré des nœuds. Ces caractéristiques conduisent toutes les deux à des matrices creuses pauvres en information tout en nécessitant beaucoup de mémoire de stockage. Dans ces travaux, nous proposons plusieurs manières de prendre en compte ces différences pour deux types de graphes particuliers. Dans la première partie, nous nous intéressons aux graphes de citations et à leur représentation dans l’optique de la veille technologique, tandis que la seconde partie s’adresse aux graphes bipartites utilisés principalement par les systèmes de recommandation. Ces adaptations permettent la réalisation de taches usuelles en apprentissage automatique, telle que le partitionnement et la visualisation des données. Pour le cas des graphes bipartites, des algorithmes spécifiques de co-partitionnement sont proposés pour la segmentation conjointe des deux parties. La troisième partie prend un revers différent. La méthode développée exploite le graphe des k plus proches voisins construit à partir des données tabulaires afin de corriger des erreurs de classifications. Les différentes méthodes développées utilisent diverses approches pour emmagasiner plus d’information dans un vecteur par rapport à l’encodage binaire habituel, permettant de travailler les graphes avec des algorithmes usuel d’apprentissage automatique
This thesis proposes new approaches to process graph using machine learning algorithms designed for tabular data. A graph is a data structure made of nodes linked to each others by edges. This structure can be represented under a matrix form where the connection between two nodes is represented by a non-zero value, simplifying the manipulation of the data. Nonetheless, the transposition of an algorithm adapted to tabular data to graphs would not give the expected results because of the structural differences. Two characteristics make the transposition difficult: the low nodes’ connectivity and the power-law distribution of nodes’ degree. These two characteristics both lead to sparse matrices with low information content while requiring a large memory. In this work, we propose several methods that consider these two graph’s specificities. In the first part, we focus on citation graphs which belong to the directed acyclic graph category and can be exploited for technical watch, while the second part is dedicated to bipartite graphs mainly use by recommender systems. These adaptations permit the achievement of usual machine learning tasks, such as clustering and data visualization. Specific co-clustering algorithms were designed to segment jointly each side of a bipartite graph and identify groups of similar nodes. The third part approaches graphs from a different perspective. The developed approach exploits the k nearest neighbours graph built from the tabular data to help correcting classification errors. These different methods use diverse methods to embed more information in a vector compared to the usual binary encoding, allowing to process graphs with usual machine learning algorithm
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Marshall, Oliver. "Search Engine Optimization and the connection with Knowledge Graphs." Thesis, Högskolan i Gävle, Företagsekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-35165.

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Aim: The aim of this study is to analyze the usage of Search Engine Optimization and Knowledge Graphs and the connection between them to achieve profitable business visibility and reach. Methods: Following a qualitative method together with an inductive approach, ten marketing professionals were interviewed via an online questionnaire. To conduct this study both primary and secondary data was utilized. Scientific theory together with empirical findings were linked and discussed in the analysis chapter. Findings: This study establishes current Search Engine Optimization utilization by businesses regarding common techniques and methods. We demonstrate their effectiveness on the Google Knowledge Graph, Google My Business and resulting positive business impact for increased visibility and reach. Difficulties remain in accurate tracking procedures to analyze quantifiable results. Contribution of the thesis: This study contributes to the literature of both Search Engine Optimization and Knowledge Graphs by providing a new perspective on how these subjects have been utilized in modern marketing. In addition, this study provides an understanding of the benefits of SEO utilization on Knowledge Graphs. Suggestions for further research: We suggest more extensive investigation on the elements and utilization of Knowledge Graphs; how the structure can be affected; which techniques are most effective on a bigger scale and how effectively the benefits can be measured. Key Words: Search Engine, Search Engine Optimization, SEO, Knowledge Graphs, Google My Business, Google Search Engine, Online Marketing.
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Moens, Theodore Warren Bernelot. "Approaches to procedural adequacy in logic programming using connection graphs." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/26499.

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Kowalski's connection graph method provides a representation for logic programs which allows for the incorporation of better procedural control techniques than standard logic programming languages. A proposed search strategy for visual recognition which combines top-down and bottom-up techniques has been incorporated in a connection graph implementation. The connection graph representation also allows for the natural incorporation of constraint satisfaction techniques in logic programming. Kowalski's approach to incorporating constraint satisfaction techniques in connection graphs is examined in detail. It is shown that his approach is not efficient enough to be used as a general preprocessing algorithm but that a modified version may be of use. Increased control of search and the incorporation of consistency techniques increase the procedural adequacy of logic programs for representing knowledge without compromising the descriptive capacity of the form.
Science, Faculty of
Computer Science, Department of
Graduate
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Hennayake, Kamal P. "Generalized edge connectivity in graphs." Morgantown, W. Va. : [West Virginia University Libraries], 1998. http://etd.wvu.edu/templates/showETD.cfm?recnum=383.

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Thesis (Ph. D.)--West Virginia University, 1998.
Title from document title page. Document formatted into pages; contains v, 87 p. : ill. Includes abstract. Includes bibliographical references (p. 64-72).
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Camby, Eglantine. "Connecting hitting sets and hitting paths in graphs." Doctoral thesis, Universite Libre de Bruxelles, 2015. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209048.

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Dans cette thèse, nous étudions les aspects structurels et algorithmiques de différents problèmes de théorie des graphes. Rappelons qu’un graphe est un ensemble de sommets éventuellement reliés par des arêtes. Deux sommets sont adjacents s’ils sont reliés par une arête.

Tout d’abord, nous considérons les deux problèmes suivants :le problème de vertex cover et celui de dominating set, deux cas particuliers du problème de hitting set. Un vertex cover est un ensemble de sommets qui rencontrent toutes les arêtes alors qu’un dominating set est un ensemble X de sommets tel que chaque sommet n’appartenant pas à X est adjacent à un sommet de X. La version connexe de ces problèmes demande que les sommets choisis forment un sous-graphe connexe. Pour les deux problèmes précédents, nous examinons le prix de la connexité, défini comme étant le rapport entre la taille minimum d’un ensemble répondant à la version connexe du problème et celle d’un ensemble du problème originel. Nous prouvons la difficulté du calcul du prix de la connexité d’un graphe. Cependant, lorsqu’on exige que le prix de la connexité d’un graphe ainsi que de tous ses sous-graphes induits soit borné par une constante fixée, la situation change complètement. En effet, pour les problèmes de vertex cover et de dominating set, nous avons pu caractériser ces classes de graphes pour de petites constantes.

Ensuite, nous caractérisons en termes de dominating sets connexes les graphes Pk- free, graphes n’ayant pas de sous-graphes induits isomorphes à un chemin sur k sommets. Beaucoup de problèmes sur les graphes sont étudiés lorsqu’ils sont restreints à cette classe de graphes. De plus, nous appliquons cette caractérisation à la 2-coloration dans les hypergraphes. Pour certains hypergraphes, nous prouvons que ce problème peut être résolu en temps polynomial.

Finalement, nous travaillons sur le problème de Pk-hitting set. Un Pk-hitting set est un ensemble de sommets qui rencontrent tous les chemins sur k sommets. Nous développons un algorithme d’approximation avec un facteur de performance de 3. Notre algorithme, basé sur la méthode primal-dual, fournit un Pk-hitting set dont la taille est au plus 3 fois la taille minimum d’un Pk-hitting set.
Doctorat en Sciences
info:eu-repo/semantics/nonPublished

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Books on the topic "Connection graph"

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Li, Xueliang, and Yuefang Sun. Rainbow Connections of Graphs. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-3119-0.

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Li, Xueliang. Rainbow Connections of Graphs. Boston, MA: Springer US, 2012.

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W, Beineke Lowell, and Wilson Robin J, eds. Graph connections: Relationships between graph theory and other areas of mathematics. Oxford: Clarendon Press, 1997.

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Conference on Graph Connections (1998 Cochin, India). Proceedings of the Conference on Graph Connections, January 28-31, 1998, Cochin. Edited by Balakrishnan R, Mulder H. M, and Vijayakumar A. New Delhi: Allied Publishers, 1999.

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W, Hayden Robert, Santoro Karen, and Sloyer Clifford W, eds. Math connections: Algebra 1 : data analysis, functions, and graphs. 2nd ed. Armonk, NY: It's About Time, 2009.

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Alberto, Corso, and Polini Claudia 1966-, eds. Commutative algebra and its connections to geometry: Pan-American Advanced Studies Institute, August 3--14, 2009, Universidade Federal de Pernambuco, Olinda, Brazil. Providence, R.I: American Mathematical Society, 2011.

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Jarvis, Jennifer. Social Connection Physical Distancing: Graph Paper Notebook, 1 Cm. Graph, Paper Dimension 6 X 9 Inches, Soft Matte Cover. Independently Published, 2020.

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Coolen, A. C. C., A. Annibale, and E. S. Roberts. Introduction. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0001.

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This introductory chapter sets the scene for the material which follows by briefly introducing the study of networks and describing their wide scope of application. It discusses the role of well-specified random graphs in setting network science onto a firm scientific footing, emphasizing the importance of well-defined null models. Non-trivial aspects of graph generation are introduced. An important distinction is made between approaches that begin with a desired probability distribution on the final graph ensembles and approaches where the graph generation process is the main object of interest and the challenge is to analyze the expected topological properties of the generated networks. At the core of the graph generation process is the need to establish a mathematical connection between the stochastic graph generation process and the stationary probability distribution to which these processes evolve.
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Jarvis, Jennifer. Social Connection Physical Distancing: Graph Paper Notebook, Journal, Diary, 4 X 4 per Sq. in. Graph, Dimension 6 X 9 Inches, Soft Matte Cover. Independently Published, 2020.

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Li, Xueliang, and Yuefang Sun. Rainbow Connections of Graphs. Springer, 2012.

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Book chapters on the topic "Connection graph"

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Li, Xueliang, Yongtang Shi, and Ivan Gutman. "The Chemical Connection." In Graph Energy, 11–17. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-4220-2_2.

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Hähnle, Reiner, Neil V. Murray, and Erik Rosenthal. "Ordered Resolution vs. Connection Graph resolution." In Automated Reasoning, 182–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45744-5_14.

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Chung, Fan, and Wenbo Zhao. "Ranking and Sparsifying a Connection Graph." In Lecture Notes in Computer Science, 66–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30541-2_6.

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Li, Xueliang, and Yuefang Sun. "Rainbow Connection Numbers of Graph Products." In SpringerBriefs in Mathematics, 73–76. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-3119-0_6.

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Even, S., and G. Granot. "Grid layouts of block diagrams — bounding the number of bends in each connection (extended abstract)." In Graph Drawing, 64–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-58950-3_357.

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Jusko, Jan, and Martin Rehak. "Revealing Cooperating Hosts by Connection Graph Analysis." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 241–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36883-7_15.

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Li, Xueliang, and Yuefang Sun. "Rainbow Connection Numbers of Some Graph Classes." In SpringerBriefs in Mathematics, 65–72. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-3119-0_5.

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Dall’Aglio, Marco, Vito Fragnelli, and Stefano Moretti. "Orders of Criticality in Graph Connection Games." In Lecture Notes in Computer Science, 35–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-662-60555-4_3.

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Parmar, Dharamvirsinh, and Bharat Suthar. "Rainbow Vertex Connection Number of a Class of Triangular Snake Graph." In Recent Advancements in Graph Theory, 329–38. Boca Raton : CRC Press, 2020. | Series: Mathematical engineering, manufacturing, and management sciences: CRC Press, 2020. http://dx.doi.org/10.1201/9781003038436-27.

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Bao, Siqi, Pei Wang, and Albert C. S. Chung. "3D Randomized Connection Network with Graph-Based Inference." In Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 47–55. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67558-9_6.

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Conference papers on the topic "Connection graph"

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Melo, Alexsander A. de, Celina M. H. de Figueiredo, Uéverton S. Souza, and Ana Silva. "On (in)tractability of connection and cut problems." In Concurso de Teses e Dissertações. Sociedade Brasileira de Computação - SBC, 2023. http://dx.doi.org/10.5753/ctd.2023.229754.

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This work addresses connection and cut problems from the viewpoint of graph classes and computational complexity, classic and parameterized. Regarding connection problems, we investigate the so-called TERMINAL CONNECTION problem (TCP), which can be seen as a generalisation of the classical STEINER TREE problem. We propose several complexity results for TCP, when restricted to specific graph classes, and some of its input parameters are fixed. As for cut problems, we analyse the complexity of the classical MAXCUT problem. We introduce the first complexity classification for the problem on interval graphs of bounded interval count. In addition, we prove the NP-completeness of MAXCUT on permutation graphs, settling a question posed by David S. Johnson in the Ongoing Guide to NP-completeness, which has been open since 1985. Finally, we consider the problem of computing the zig-zag number of a directed graph, which is a directed width measure defined over cuts of a graph.
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Lubis, H., N. M. Surbakti, R. I. Kasih, D. R. Silaban, and K. A. Sugeng. "Rainbow connection and strong rainbow connection of the crystal graph and neurons graph." In PROCEEDINGS OF THE 4TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES (ISCPMS2018). AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5132480.

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Anadiotis, Angelos Christos, Ioana Manolescu, and Madhulika Mohanty. "Integrating Connection Search in Graph Queries." In 2023 IEEE 39th International Conference on Data Engineering (ICDE). IEEE, 2023. http://dx.doi.org/10.1109/icde55515.2023.00200.

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Rocha, Aleffer, Sheila M. Almeida, and Leandro M. Zatesko. "The Rainbow Connection Number of Triangular Snake Graphs." In Encontro de Teoria da Computação. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/etc.2020.11091.

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Rainbow coloring problems, of noteworthy applications in Information Security, have been receiving much attention last years in Combinatorics. The rainbow connection number of a graph G is the least number of colors for a (not necessarily proper) edge coloring of G such that between any pair of vertices there is a path whose edge colors are all distinct. In this paper we determine the rainbow connection number of the triple triangular snake graphs.
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Niu, Lingfeng, Jianmin Wu, and Yong Shi. "Entity Resolution with Attribute and Connection Graph." In 2011 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2011. http://dx.doi.org/10.1109/icdmw.2011.75.

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Zhao, Wenting, Yuan Fang, Zhen Cui, Tong Zhang, and Jian Yang. "Graph Deformer Network." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/227.

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Convolution learning on graphs draws increasing attention recently due to its potential applications to a large amount of irregular data. Most graph convolution methods leverage the plain summation/average aggregation to avoid the discrepancy of responses from isomorphic graphs. However, such an extreme collapsing way would result in a structural loss and signal entanglement of nodes, which further cause the degradation of the learning ability. In this paper, we propose a simple yet effective Graph Deformer Network (GDN) to fulfill anisotropic convolution filtering on graphs, analogous to the standard convolution operation on images. Local neighborhood subgraphs (acting like receptive fields) with different structures are deformed into a unified virtual space, coordinated by several anchor nodes. In the deformation process, we transfer components of nodes therein into affinitive anchors by learning their correlations, and build a multi-granularity feature space calibrated with anchors. Anisotropic convolutional kernels can be further performed over the anchor-coordinated space to well encode local variations of receptive fields. By parameterizing anchors and stacking coarsening layers, we build a graph deformer network in an end-to-end fashion. Theoretical analysis indicates its connection to previous work and shows the promising property of graph isomorphism testing. Extensive experiments on widely-used datasets validate the effectiveness of GDN in graph and node classifications.
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Onur, Şeyma, and Gökşen Bacak Turan. "Geodetic Domination Integrity of Transformation Graphs." In 6th International Students Science Congress. Izmir International Guest Student Association, 2022. http://dx.doi.org/10.52460/issc.2022.030.

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The concept of domination has a wide field of research in graph theory. The dominating set of a graph G is a subset S of vertices of G such that every vertex not in S is adjacent to at least one vertex in S [1]. The concept of domination has various types defined on vertices and edges. If each vertex in a dominating set S of the graph G is also a member of the geodetic set, then the set S is called a geodetic dominating set [2]. A communication network is a connection between centers and those centers that allow them to communicate with each other it consists of lines. These network centers can be modeled as the vertices of the graph and the connecting lines as the edges of the graph. Some parameters have been defined to measure the vulnerability of the graph in case some vertex or edge of the graph modeling a communication network is damaged. One of these parameters is the geodetic domination integrity [3]. In this study, the geodetic domination integrity of graphs is considered, and some general results are obtained for the geodetic domination integrity of some transformation graphs.
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Surbakti, N. M., D. R. Silaban, and K. A. Sugeng. "The rainbow connection number of graph resulting for operation of sun graph and path graph." In PROCEEDINGS OF THE 5TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES (ISCPMS2019). AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0007807.

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Zhao, Yan, Shasha Li, and Sujuan Liu. "(Strong) Rainbow Connection Number of Line, Middle and Total Graph of Sunlet Graph." In 2018 IEEE International Conference on Progress in Informatics and Computing (PIC). IEEE, 2018. http://dx.doi.org/10.1109/pic.2018.8706299.

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Zhang, Zaixi, Qi Liu, Zhenya Huang, Hao Wang, Chengqiang Lu, Chuanren Liu, and Enhong Chen. "GraphMI: Extracting Private Graph Data from Graph Neural Networks." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/516.

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As machine learning becomes more widely used for critical applications, the need to study its implications in privacy becomes urgent. Given access to the target model and auxiliary information, model inversion attack aims to infer sensitive features of the training dataset, which leads to great privacy concerns. Despite its success in the grid domain, directly applying model inversion techniques on non grid domains such as graph achieves poor attack performance due to the difficulty to fully exploit the intrinsic properties of graphs and attributes of graph nodes used in GNN models. To bridge this gap, we present Graph Model Inversion attack, which aims to infer edges of the training graph by inverting Graph Neural Networks, one of the most popular graph analysis tools. Specifically, the projected gradient module in our method can tackle the discreteness of graph edges while preserving the sparsity and smoothness of graph features. Moreover, a well designed graph autoencoder module can efficiently exploit graph topology, node attributes, and target model parameters. With the proposed method, we study the connection between model inversion risk and edge influence and show that edges with greater influence are more likely to be recovered. Extensive experiments over several public datasets demonstrate the effectiveness of our method. We also show that differential privacy in its canonical form can hardly defend our attack while preserving decent utility.
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Reports on the topic "Connection graph"

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Hrebeniuk, Bohdan V. Modification of the analytical gamma-algorithm for the flat layout of the graph. [б. в.], December 2018. http://dx.doi.org/10.31812/123456789/2882.

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The planarity of graphs is one of the key sections of graph theory. Although a graph is an abstract mathematical object, most often it is graph visualization that makes it easier to study or develop in a particular area, for example, the infrastructure of a city, a company’s management or a website’s web page. In general, in the form of a graph, it is possible to depict any structures that have connections between the elements. But often such structures grow to such dimensions that it is difficult to determine whether it is possible to represent them on a plane without intersecting the bonds. There are many algorithms that solve this issue. One of these is the gamma method. The article identifies its problems and suggests methods for solving them, and also examines ways to achieve them.
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Ratwani, Raj M., J. G. Trafton, and Deborah A. Boehm-Davis. Thinking Graphically: Connecting Vision and Cognition during Graph Comprehension. Fort Belvoir, VA: Defense Technical Information Center, January 2008. http://dx.doi.org/10.21236/ada479715.

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Sondheim, M., and C. Hodgson. Common hydrology features (CHyF) logical model. Natural Resources Canada/CMSS/Information Management, 2024. http://dx.doi.org/10.4095/328952.

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The Open Geospatial Consortium has defined "OGC WaterML 2: Part 3 - Surface Hydrology Features (HY_Features) - Conceptual Model", but not any particular implementation of it. The Common Hydrology Features (CHyF) model extends HY_Features and makes some minor changes to it required for implementation and the delivery of high performance services. HY_Features discusses catchment coverage and topological relations. In CHyF these are key ideas, as is the notion that hydrologically defined network components form elements of a mathematical graph, allowing for very fast network traversal. HY_Features defines catchments and catchment networks, as well as rivers, channels, flowpaths and hydrographic networks. The CHyF logical model specifies a profile and some extensions to HY_Features, as required to implement topological and graph relations. This starts with the definition of elementary catchments and elementary flowpaths, which are treated as fundamental elements. They are tightly specified terms corresponding to basic catchments and flowpaths in HY_Features and the basic components in the standard reach-catchment model (Maidment and Clark, 2016). If they are subdivided, the result is simply more elementary catchments and elementary flowpaths. Consequently, they are the building blocks used to form complementary coverages as well as a graph structure referred to as a hygraph. Building the hygraph necessitates that connections between features be manifest through their geometry. Divergences and distributaries are supported in CHyF, as the hygraph need not be hierarchical. Nevertheless, CHyF does recognize hierarchical drainage basins and the value in identifying them explicitly (Blodgett, et al, 2021). Different kinds of elementary catchments and elementary flowpaths are defined in CHyF. Of note is that polygonal waterbody features, or portions of such features, are treated as elementary catchments in their own right. In addition to these water catchments, several kinds of land-based elementary catchments are recognized. These model constructs are compatible with the higher level conceptual model in HY_Features, although they differ in detail from other popular implementation models. With the approach taken it becomes practical to handle very large lakes and rivers, as well as coastal ocean zones. CHyF also includes wetlands, glaciers and snowfields as kinds of hydro features; these features help complete the concept of a catchment coverage as put forward by HY_Features.
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