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. . Algorithms:. Graph . coloring. Created by: . . . Avdeev. . Alex,. . . Blakey Paul.. Criteria for good graph coloring algorithm:. Coloring Quality: . Number of colors needed . Number of colors ( . Adapted from UMD Jimmy Lin’s slides, which . is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United . States. See . http://. creativecommons.org. /licenses/by-. nc. -. Arijit. Khan, Nan Li, . Xifeng. Yan, . Ziyu. Guan. Computer Science . UC Santa Barbara. {. arijitkhan. , . nanli. , . xyan. , . ziyuguan. }@. cs.ucsb.edu. . Supriyo. Chakraborty. UC Los Angeles. Lei Shi, Sibai Sun, . Yuan Xuan. , Yue Su, . Hanghang . Tong, Shuai Ma, Yang . Chen. Influence Graph. Initial. Tweet. Re-tweeting Graph. Re-tweets. Citing papers. Source. Paper. Paper Citation Graph. - Week 13. 2. Problem: Laying Telephone Wire. Central office. 3. Wiring: Naive Approach. Central office. Expensive!. 4. Wiring: Better Approach. Central office. Minimize the total length of wire connecting . 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. Points, Bridges, . Bi-connectivity. “Critical nodes, critical edges” and connectivity. Ivaylo. . Kenov. Telerik Corporation. http:/telerikacademy.com. Telerik. Academy Student. Table of Contents. 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.. Sushmita Roy. sroy@biostat.wisc.edu. Computational Network Biology. Biostatistics & Medical Informatics 826. Computer Sciences 838. https://compnetbiocourse.discovery.wisc.edu. Nov 1. st. 2016. Some material is adapted from lectures from Introduction to Bioinformatics. 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.