PPT-Graph

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. 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. Xiaoming. Sun and David P. Woodruff. Chinese Academy of Sciences and IBM Research-. Almaden. Streaming Models. Long sequence of items appear one-by-one. numbers, points, edges, …. (usually) . adversarially. 1. Graph Algorithms. Many problems are naturally represented as graphs. Networks, Maps, Possible paths, Resource Flow, etc.. Ch. 3 focuses on algorithms to find connectivity in graphs. Ch. 4 focuses on algorithms to find paths within graphs. Chien. -chi Chen. 1. Outline. 2. Introduction. Interactive segmentation. Related work. Graph cut. Concept of graph cut. Hard and smooth constrains. Min cut/Max flow. Extensive of Graph cut. Grab cut. 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. 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 . Drummond Reed. 2012-02-06. This document contains illustrations of basic XDI graph patterns:. I-names, . i. -numbers, and synonyms:. XDI statements used to assert multiple . XRIs. for the same logical resource. 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. 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. Adjacency List. The sum of the lengths of the adjacency lists is 2|E| in an undirected graph, and |E| in a directed graph.. Graph Algorithms Lecture 19 CS 2110 — Spring 2019 JavaHyperText Topics “Graphs”, topics: 4: DAGs, topological sort 5: Planarity 6: Graph coloring 2 Announcements Monday after Spring Break there will be a Data Structures and Algorithms. CSE 373 19 SP - Kasey Champion. 1. Administrivia. We clarified Exercise 5 Problem [] to explicitly mention “worst-case”. CSE 373 SP 18 - Kasey Champion. 2. Administrivia. Data Structures and Algorithms. CSE 373 WI 19 - Kasey Champion. 1. Last Time. We described algorithms to find:. CSE 373 SP 18 - Kasey Champion. 2. An ordering of the vertices so all edges go from left to right. . Data Structures and Algorithms. CSE 373 19 . Sp. - Kasey Champion. 1. Administrivia. HW 7 Due Friday. Final exam review Wednesday 6/5 4-5:50. Final exam next Tuesday!. Double check all grades . Please fill out survey. Outline . Definition and Data Structures of Graph. . Eulerian. & Hamiltonian Cycle . . DNA Sequencing . . Shortest Superstring Problem, SSP as. . Traveling. . Salesman Problem (TSP) . Sequencing by Hybridization (SBH), SBH as Hamiltonian .