'Subgraph isomorphism' presentation slideshows

Emerging Graph Queries in Linked Data

Emerging Graph Queries in Linked Data. Arijit Khan, Yinghui Wu, Xifeng Yan Department of Computer Science University of California, Santa Barbara { arijitkhan , yinghui , xyan }@ cs.ucsb.edu. Graph Data. Graphs are everywhere. Ecological Network. Biological Network. Social Network.

1.13k views • 100 slides

Shuai Ma

Graph Search & Social Networks. Shuai Ma. Graphs are everywhere , and quite a few are huge graphs!. Application Scenarios. Software plagiarism detection [1]. Traditional plagiarism detection tools may not be applicable for serious software plagiarism problems.

704 views • 61 slides

Subgraph Search Over Large Graph Database

?????????????? Institute of Computer Science and Technology of Peking University. Subgraph Search Over Large Graph Database. Instructor: Lei Zou. Outline. Subgraph Isomorphism Algorihtm Ullmann Algorithm; VF2 Algorithm QuickSI

723 views • 58 slides

SubSea: An Efficient Heuristic Algorithm for Subgraph Isomorphism

SubSea: An Efficient Heuristic Algorithm for Subgraph Isomorphism. Vladimir Lipets Ben-Gurion University of the Negev Joint work with Prof. Ehud Gudes. Motivation. Subgraph isomorphism is important and very general form of pattern matching that finds practical application in areas such as:

495 views • 43 slides

EECS 800 Research Seminar Mining Biological Data

EECS 800 Research Seminar Mining Biological Data. Instructor: Luke Huan Fall, 2006. Overview. A quick review of PCA Graph mining in microarray analysis Graph indexing. Data Matrix. The data matrix: where is a column vector is the column mean of. Projection.

523 views • 42 slides

EECS 800 Research Seminar Mining Biological Data

EECS 800 Research Seminar Mining Biological Data. Instructor: Luke Huan Fall, 2006. Overview. A quick review of PCA Graph mining in microarray analysis Graph indexing. Data Matrix. The data matrix: where is a column vector is the column mean of. Projection.

427 views • 42 slides

Seminar in Bioinformatics

Seminar in Bioinformatics. An efficient algorithm for detecting frequent subgraphs in biological networks. Paper by: M. Koyuturk, A. Grama and W. Szpankowski Appeared in: Bioinformatics, Vol. 20, Sup. 1, 2004, pages i200-i207. Presented by: Royi Ronen. Abstract. Motivation

520 views • 41 slides

404 views • 29 slides

Graph Databases: Efficient storage ? and Rapid retrieval ?

Graph Databases: Efficient storage ? and Rapid retrieval ?. Robert Levinson Machine Intelligence Laboratory University of California Santa Cruz. THE CG MARS LANDER. English-CG-English Translation. High level architecture. English Discourse. English Queries.

340 views • 24 slides

Two subgraph maximization problems

Two subgraph maximization problems. Michael Langberg. Open University Israel. Joint with Guy Kortsarz, Zeev Nutov, Yuval Rabani and Chaitanya Swamy. This talk: overview. Two maximization problems. Not addressed in the past (in this context). Part I : Subgraph homomorphism .

340 views • 24 slides

Incremental Graph Pattern Matching

Incremental Graph Pattern Matching. Outline. Graph pattern matching in real-life scenario graph pattern matching is expensive Real life graphs are changing over time Incremental graph pattern matching Simulation, bounded simulation and subgraph isomorphism

560 views • 24 slides

Graph Databases: Efficient storage ? and Rapid retrieval ?

Graph Databases: Efficient storage ? and Rapid retrieval ?. Robert Levinson Machine Intelligence Laboratory University of California Santa Cruz. THE CG MARS LANDER. English-CG-English Translation. High level architecture. English Discourse. English Queries.

248 views • 24 slides

Action Planning for Graph Transition Systems

Action Planning for Graph Transition Systems. Stefan Edelkamp Shahid Jabbar Computer Science Department University of Dortmund, Dortmund, Germany Alberto Lluch-Lafuente Department of Informatics, University of Pisa, Pisa, Italy. Graph Transition Systems. Graph Transition Systems.

343 views • 22 slides

Towards Graph Containment Search and Indexing

Towards Graph Containment Search and Indexing. Chen Chen 1 , Xifeng Yan 2 , Philip S. Yu 2 , Jiawei Han 1 , Dong-Qing Zhang 3 , Xiaohui Gu 2 1 University of Illinois at Urbana-Champaign 2 IBM T.J. Watson Research Center 3 Thomson Research

226 views • 13 slides