Pattern-based visual subgraph query formulation meets query processing

Nowadays, graph is used in many applications because it provides natural ways to represent data. But not all the users who need to work with graph database are IT-experts to use complicated system for querying graph database. PRAGUE is a framework that provides user a friendly GUI and efficie...

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Main Author: Nguyen, Hong Hien.
Other Authors: Sourav Saha Bhowmick
Format: Final Year Project
Language:English
Published: 2012
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Online Access:http://hdl.handle.net/10356/49065
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-490652023-03-03T20:25:58Z Pattern-based visual subgraph query formulation meets query processing Nguyen, Hong Hien. Sourav Saha Bhowmick School of Computer Engineering Centre for Advanced Information Systems DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition Nowadays, graph is used in many applications because it provides natural ways to represent data. But not all the users who need to work with graph database are IT-experts to use complicated system for querying graph database. PRAGUE is a framework that provides user a friendly GUI and efficient System Response Time (SRT) to query graph database. PRAGUE interleaves visual query graph formulation and processing by exploiting the latency offered by the GUI to remove false matches and pre-fetch partial results. By using SPIG to store all possible connected subgraph of the query, the system can handle both exact and similar subgraph matching. To make framework more useful and friendly, there is a need to enhance it to allow user build queries from given patterns. PRAGUE cannot handle pattern-based query processing efficiently because it cannot simulate the process when user drags and drops in a pattern, which leads to very large SRT. Moreover, the query formulated from pattern is often large, which leads to explosive increase in size of SPIG set and make PRAGUE inefficient in term of memory. By introducing the concepts of pattern-based view of graph, in this report, we overcome the system response time limitation and memory limitation of PRAGUE when processing queries formulated from pattern. Moreover, inspired by the need of selecting the best set of patterns to display on the very limited space of GUI, we propose a novel algorithm to generate patterns by mining from graph database, and then select the best subset from that in order to display on GUI. Bachelor of Engineering (Computer Science) 2012-05-14T07:28:51Z 2012-05-14T07:28:51Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/49065 en Nanyang Technological University 65 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
Nguyen, Hong Hien.
Pattern-based visual subgraph query formulation meets query processing
description Nowadays, graph is used in many applications because it provides natural ways to represent data. But not all the users who need to work with graph database are IT-experts to use complicated system for querying graph database. PRAGUE is a framework that provides user a friendly GUI and efficient System Response Time (SRT) to query graph database. PRAGUE interleaves visual query graph formulation and processing by exploiting the latency offered by the GUI to remove false matches and pre-fetch partial results. By using SPIG to store all possible connected subgraph of the query, the system can handle both exact and similar subgraph matching. To make framework more useful and friendly, there is a need to enhance it to allow user build queries from given patterns. PRAGUE cannot handle pattern-based query processing efficiently because it cannot simulate the process when user drags and drops in a pattern, which leads to very large SRT. Moreover, the query formulated from pattern is often large, which leads to explosive increase in size of SPIG set and make PRAGUE inefficient in term of memory. By introducing the concepts of pattern-based view of graph, in this report, we overcome the system response time limitation and memory limitation of PRAGUE when processing queries formulated from pattern. Moreover, inspired by the need of selecting the best set of patterns to display on the very limited space of GUI, we propose a novel algorithm to generate patterns by mining from graph database, and then select the best subset from that in order to display on GUI.
author2 Sourav Saha Bhowmick
author_facet Sourav Saha Bhowmick
Nguyen, Hong Hien.
format Final Year Project
author Nguyen, Hong Hien.
author_sort Nguyen, Hong Hien.
title Pattern-based visual subgraph query formulation meets query processing
title_short Pattern-based visual subgraph query formulation meets query processing
title_full Pattern-based visual subgraph query formulation meets query processing
title_fullStr Pattern-based visual subgraph query formulation meets query processing
title_full_unstemmed Pattern-based visual subgraph query formulation meets query processing
title_sort pattern-based visual subgraph query formulation meets query processing
publishDate 2012
url http://hdl.handle.net/10356/49065
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