PPT-Graph Algorithm:

Breadth First Search Nattee Niparnan Distance of nodes The distance between two nodes is the length of the shortest path between them S A 1 S C 1 S B 2 DFS and Length. Why graph clustering is useful?. Distance matrices are graphs .  as useful as any other clustering. Identification of communities in social networks. Webpage clustering for better data management of web data. by . Matchings. . Tobias . Mömke. and Ola Svensson. KTH Royal Institute of Technology. Sweden. Travelling Salesman Problem. Given . . n. . cities . distance. . d(u,v. ) . between . c. ities. . Implement a graph in three ways:. Adjacency List. Adjacency-Matrix. Pointers/memory for each node (actually a form of adjacency list). Adjacency List. List of pointers for each vertex. Undirected Adjacency List. P. artitioning. a. nd. . Clustering for. Community . Detection. . Presented By: Group One. 1. Outline. Introduction:  . Hong . Hande. Graph Partitioning: . Muthu. Kumar . C . and . Xie . Shudong. April 10, 2012. Parallel Graph Algorithms. Aydın . Buluç. ABuluc@lbl.gov. Lawrence Berkeley National Laboratory. Some slides from: . Kamesh. . Madduri. , John Gilbert, Daniel . Delling. . Graph Preliminaries. . Γραφημάτων . Διάλεξη . 3. Τριγωνικά Γραφήματα. Μεταβατικά Γραφήματα. Σταύρος Δ. Νικολόπουλος. 1. . . . Triangulated Graphs. What is a graph? . In simple words, . A graph is a set of vertices and edges which connect them.. A node (or vertex) is a discrete position in the graph. . An edge (or connection) is a link between two vertices. 2. Overview. Graph Coloring Basics. Planar/4-color Graphs. Applications. Chordal Graphs. New Register Allocation Technique. 3. Basics. Assignment of . "colors". to certain objects in a . graph. subject to certain constraints. By Clara Bryant. How a Human solves a Maze. Greek Myth of the Minotaur. Greek hero Theseus is given string to find his way through and back out of the maze. String and chalk method to solve a maze. Mark the places you’ve visited already . Implement a graph in three ways:. Adjacency List. Adjacency-Matrix. Pointers/memory for each node (actually a form of adjacency list). Adjacency List. List of pointers for each vertex. Undirected Adjacency List. Hao Wei. 1. , . Jeffrey Xu Yu. 1. , Can L. u. 1. , . Xuemin. Lin. 2. . 1 . The . Chinese University of Hong Kong, Hong Kong. 2 . The . University of New South Wales. , . Sydney, Australia. Graph in Big Data . GraphBLAS. Jeremy Kepner, Vijay . Gadepally. , Ben Miller. 2014 December. This material is based upon work supported by the National Science Foundation under Grant No. DMS-. 1312831.. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.. Mahalanobis. distance. MASTERS THESIS. By: . Rahul. Suresh. COMMITTEE MEMBERS. Dr.Stan. . Birchfield. Dr.Adam. Hoover. Dr.Brian. Dean. Introduction. Related work. Background theory: . Image as a graph. Distance matrices are graphs .  as useful as any other clustering. Identification of communities in social networks. Webpage clustering for better data management of web data. Outline. Min s-t cut problem.