'Graph structure' presentation slideshows

Bayesian Networks

Bayesian Networks. October 9, 2008 Sung-Bae Cho. Agenda. Bayesian Network Introduction Inference of Bayesian Network Modeling of Bayesian Network Bayesian Network Application Bayesian Network Application Example Life Log Application Example Summary & Review. 5 7. Probabilities.

1.36k views • 83 slides

Graph Analytics

Graph Analytics . Definition Data Structures Applications Problems Graph Pattern Matching Partitioning Distribution AKKA. Fast review on Graph and graph theory. Definition: A "graph" is a collection of " vertices" or "nodes" " edges " that connect pairs of vertices.

1.6k views • 71 slides

Constraint Satisfaction Problems

Constraint Satisfaction Problems. CHAPTER 6 Oliver Schulte Summer2011. Midterm Announcements. Please bring ID to the exam. You can bring a cheat sheet. Chapters 1-6 covered, see Lecture Schedule. CSP definition is covered, also arc consistency.

836 views • 66 slides

Web Crawlers and Link Analysis

Web Crawlers and Link Analysis. David Kauchak cs458 Fall 2011 adapted from: http://www.stanford.edu/class/cs276/handouts/ lecture15-linkanalysis.ppt http://webcourse.cs.technion.ac.il/236522/Spring2007/ho/WCFiles/Tutorial05.ppt. Administrative. Midterm Timeline

726 views • 54 slides

Lecture 06

627 views • 48 slides

Replication-based Fault-tolerance for Large-scale Graph Processing

508 views • 35 slides

Jimmy Lin The iSchool University of Maryland Wednesday, February 6, 2008

Cloud Computing Lecture #4 Graph Algorithms with MapReduce. Jimmy Lin The iSchool University of Maryland Wednesday, February 6, 2008.

626 views • 33 slides

The Union-Split Algorithm and Cluster-Based Anonymization of Social Networks

The Union-Split Algorithm and Cluster-Based Anonymization of Social Networks. Brian Thompson Danfeng Yao. Rutgers University Dept. of Computer Science Piscataway, NJ, USA. Contributions. A novel graph anonymization technique that

448 views • 32 slides

You Are What You Link

442 views • 31 slides

Measurement and Analysis of Online Social Networks

Measurement and Analysis of Online Social Networks. A. Mislove, M. Marcon, K Gummadi, P. Druschel, B. Bhattacharjee. Presentation by Shahan Khatchadourian Supervisor: Prof. Mariano P. Consens. Focus. graphs of online social networks how they were obtained how they were verified

519 views • 30 slides

Semantic Web

Semantic Web. Chapter 7. SPARQL: Query Language for RDF. PREFIX ex: <http://example.org/> SELECT ?title ?author WHERE { ?book ex:publishedBy <someone>. ?book ex:title ?title. ?book ex:author ?author }. Example result (Select result). Group patterns. { {?pattern thatIs <uri/simple> }

452 views • 29 slides

Eran Tromer

423 views • 27 slides

XML DOCUMENTS AND DATABASES

XML DOCUMENTS AND DATABASES. Introduction. This part is about how XML Documents can be stored and retrieved. Approaches to Storing XML Documents.

430 views • 27 slides

Integrated Maximum Flow Algorithm for Optimal Response Time Retrieval of Replicated Data

Integrated Maximum Flow Algorithm for Optimal Response Time Retrieval of Replicated Data. Nihat Altiparmak , Ali Saman Tosun The University of Texas at San Antonio. Declustering and Parallel I/O. 1 Access. Disk 0. Disk 1. Disk 2. Disk 3. Disk 4. Replication.

407 views • 26 slides

Spring 2014 BioE 2630 (Pitt) : 16-725 (CMU RI) 18-791 (CMU ECE) : 42-735 (CMU BME)

387 views • 24 slides

Graphical Multi-Task Learning

Graphical Multi-Task Learning. Dan Sheldon Cornell University NIPS SISO Workshop 12/12/2008. Multi-Task Learning (MTL). Separate but related learning tasks --- solve them jointly to achieve better performance

340 views • 23 slides

584 views • 17 slides

What is the Demographic Transition Model?

?. ?. What is the Demographic Transition Model?. Starter: Write down definitions for these terms: Birth Rate Death Rate Infant mortality Dense Sparse. ?. BY THE END OF THIS LESSON YOU WILL BE ABLE TO EXPLAIN TO ME EXACTLY WHAT THIS IS AND HOW IT WORKS. ?. ?.

403 views • 15 slides

Ming Ji Department of Computer Science University of Illinois at Urbana-Champaign

Active Learning for Information N etworks A Variance Minimization Criterion. Ming Ji Department of Computer Science University of Illinois at Urbana-Champaign. Information Networks: the Data. Information networks Abstraction: graphs

261 views • 10 slides

8. Path distances

3. Sampling the graph

76 views • 1 slides