'Query graph' presentation slideshows

CHAPTER 18 Strategies for Query Processing

CHAPTER 18 Strategies for Query Processing. Introduction. DBMS techniques to process a query Scanner identifies query tokens Parser checks the query syntax Validation checks all attribute and relation names Query tree (or query graph) created Execution strategy or query plan devised

831 views • 72 slides

Capturing User Intent for Information Retrieval

Capturing User Intent for Information Retrieval. Hien Nguyen University of Connecticut Major advisor : Dr. Eugene Santos Jr. (UCONN) Associate advisor : Dr. Robert McCartney (UCONN) Associate advisor : Dr. AnHai Doan (UIUC) Associate advisor : Dr. Robert Henning (UCONN).

731 views • 64 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

724 views • 58 slides

Lecture 14: Graph Data Mining

Lecture 14: Graph Data Mining. Slides are modified from Jiawei Han & Micheline Kamber. Graph Data Mining. DNA sequence RNA. Graph Data Mining. Compounds Texts. Outline. Graph Pattern Mining Mining Frequent Subgraph Patterns Graph Indexing Graph Similarity Search

608 views • 37 slides

Chapter 7. Query Processing

Chapter 7. Query Processing. Seoul National University Department of Computer Engineering OOPSLA Lab. CONTENTS. Introduction Traversal of Nodes in a Query Graph Cost Model. Introduction. Phases of Query Processing Query Graph Similarities between OO and Relational Queries Join Methods.

515 views • 35 slides

Chapter 7. Query Processing

Chapter 7. Query Processing. Seoul National University Department of Computer Engineering OOPSLA Lab. CONTENTS. Introduction Traversal of Nodes in a Query Graph Cost Model. Introduction. Phases of Query Processing Query Graph Similarities between OO and Relational Queries Join Methods.

510 views • 35 slides

SPARQ2L : Towards Supporting Subgraph Extraction Queries in RDF Databases

SPARQ2L : Towards Supporting Subgraph Extraction Queries in RDF Databases. Kemafor Anyanwu 1 , Angela Maduko 1 , Amit Sheth 2 1 LSDIS lab, University of Georgia 2 Kno.e.sis Center, Wright State University. Subgraph Extraction Queries. What are they?

461 views • 31 slides

Aliaksei A. Holubeu

405 views • 31 slides

Network Motif Discovery using Subgraph Enumeration and Symmetry-Breaking by Grochow and Kellis

Network Motif Discovery using Subgraph Enumeration and Symmetry-Breaking by Grochow and Kellis. Wooyoung Kim 4/3/2009 CSc 8910 Analysis of Biological Network , Spring 2009 Dr. Yi Pan. Outline. Introduction Motif-centric approach algorithm Results and Evaluation Biological Significance

304 views • 28 slides

Correlation Search in Graph Databases

Correlation Search in Graph Databases. Yiping Ke James Cheng Wilfred Ng Presented By Phani Yarlagadda. Outline. Motivation Challenges Problem Definition Solution Performance Evaluation Related Works. Motivation.

351 views • 22 slides

Correlation Search in Graph Databases

Correlation Search in Graph Databases. Yiping Ke James Cheng Wilfred Ng Presented By Phani Yarlagadda. Outline. Motivation Challenges Problem Definition Solution Performance Evaluation Related Works. Motivation.

288 views • 22 slides

An Edge-Based Framework for Fast Subgraph Matching in a Large Graph

An Edge-Based Framework for Fast Subgraph Matching in a Large Graph. Sangjae Kim Inchul Song Yoon Joon Lee DASFAA 2011. Outline. Introduction Preliminaries Pre-processing Filtering Verification Evaluation Conclusions. Introduction.

377 views • 19 slides

Avoiding Idle Waiting in the execution of Continuous Queries

Avoiding Idle Waiting in the execution of Continuous Queries. Carlo Zaniolo CSD CS240B Notes April 2008. Continuous Query Optimization. Global optimization objectives can change during execution from, e.g., Response time minimization (typical)

279 views • 18 slides

Neighborhood Based Fast Graph Search in Large Networks

Neighborhood Based Fast Graph Search in Large Networks. Arijit Khan Nan Li Xifeng Yan Ziyu Guan Supriyo Chakraborty Shu Tao SIGMOD 2011. Outlines. Motivation Objectives Methodology - Ness -Information Propagation Model Experiments Conclusions.

308 views • 17 slides

Large-Scale Malware Indexing Using Function-Call Graphs

403 views • 15 slides