PPT-Relevant Subgraph Extraction

Longin Jan Latecki Based on P Dupont J Callut G Dooms JN Monette and Y Deville Relevant subgraph extraction from random walks in a graph RR 200607 Catholic University of Louvain November 2006. There is a signi64257cant gap between the best known upper and lower bounds for this problem It is NPhard and does not have a PTAS unless NP has subexponential time algorithms On the other hand the current best known algorithm of Feige Kortsarz and One method to make your argument relevant and elegant. Relevancy. One of the most important aspect of constructing your argument (b/c your argument is from motion, and for motion to be approved or to be opposed by the adjudicator). Extracting Optimal Quasi-Cliques with Quality . Guarantees. . Charalampos (Babis) E. Tsourakakis. charalampos.tsourakakis@aalto.fi. KDD 2013. Longin Jan Latecki. Based on :. P. . Dupont. , J. . Callut. , G. Dooms, J.-N. . Monette. and Y. Deville.. Relevant subgraph extraction from random walks in a graph. . RR 2006-07, Catholic University of Louvain , November 2006.. Degree 10 0 10 1 10 2 10 3 10 4 10 5 10 0 10 2 10 4 10 6 Total Subgraph 1 Subgraph 2 Subgraph 3 Degree 10 0 10 1 10 2 10 3 10 4 10 5 Count of Degree 10 0 10 2 10 4 10 6 Total Subgraph 1 Subgraph 2 Sub Subgraphs from . Network Datasets. Manish . Gupta. UIUC. Microsoft. , India. Arun. . Mallya. , . Subhro. Roy. Jason Cho, Jiawei . Han. Motivation (1). Query based subgraph outlier detection. A security officer may like to find some tiny but . Using the Ullman Algorithm for Graphical Matching. Iddo. . Aviram. OCR- a Brief Review. Optical character recognition. , usually abbreviated to . OCR. , is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. I I Heaviestk-subgraph(HkS):Input:AweightedgraphG=(V;E),jVj=n,andanintegerk,knOutput:FindakverticessubgraphofGwiththemaximumtotaledgeweight MariaLiazi PolynomialvariantsoftheDkS/HkSproblem I Densestk Vinay Gangadhar. gangadhar@wisc.edu. . ECE 751 Talk, Fall 2015. Department of Electrical and Computer Engineering. UW- Madison. 1. Background. 2. Embedded workloads – Computationally demanding. Mobile processors . (and related problems). on Minor-Free Graphs. Hans . Bodlaender. (U Utrecht, TU Eindhoven). Jesper. . Nederlof. (TU Eindhoven). Tom van der . Zanden. (U Utrecht). 1. Subgraph Isomorphism. Given: a . Matching on Large Graphs in Cloud. Zhao Chang*, Lei . Zou. †, . Feifei. Li*. *University of Utah, USA . †. Peking University, China. Outline. Background. K-. Automorphism. Subgraph. Matching. Extracting Optimal Quasi-Cliques with Quality . Guarantees. . Charalampos (Babis) E. Tsourakakis. charalampos.tsourakakis@aalto.fi. KDD 2013. Extracting from template-based data. An example on how this data is generated. Querying on Amazon by filling in a form interface using . Jignesh. Patel. The query goes to a database in the backend. Database result is plugged into template-based pages. Dr .Mohammed Alaraji. BDS,FIBMS. Extraction of teeth is the most important part of minor oral surgery and the most common procedure to general dental practitioner (dentist). . Definition. Exodontia is a painless removal of teeth from their bony alveolar socket with relatively minimal amount of trauma to the investing or surrounding tissues, so that the wound may heal without postoperative problems..