primary research team & capabilities
DESCRIPTION
Primary Research Team & Capabilities. URL: http://ikt.ui.sav.sk. Dept. of Parallel and Distributed Computing Research and Development Areas: Large-scale HPCN, Grid and MapReduce applications Intelligent and Knowledge oriented Technologies Experience from IST: - PowerPoint PPT PresentationTRANSCRIPT
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Primary Research Team & CapabilitiesPrimary Research Team & Capabilities
Dept. of Parallel and Distributed ComputingResearch and Development Areas:
– Large-scale HPCN, Grid and MapReduce applications– Intelligent and Knowledge oriented Technologies
Experience from IST:– 3 project in FP5: ANFAS, CrosGRID, Pellucid– 6 project in FP6: EGEE II, K-Wf Grid, DEGREE
(coordinator), EGEE, int.eu.grid, MEDIGRID– 4 projects in FP7: Commius, Admire, Secricom, EGEE III
Several National Projects (SPVV, VEGA, APVT)IKT Group Focus:
– Information Processing (Large Scale)– Graph Processing – Information Extraction and Retrieval– Semantic Web– Knowledge oriented Technologies– Parallel and Distributed Information Processing
Solutions:– SGDB: Simple Graph Database– gSemSearch: Graph based Semantic Search– Ontea: Pattern-based Semantic Annotation– ACoMA: KM tool in Email– EMBET: Recommendation System– Experts on MapReduce and IR (Nutch, Solr, Lucene)
Director & leader of PDC: Dr. Ladislav Hluchý
URL: http://ikt.ui.sav.sk
Approach and SolutionsApproach and Solutions
Large scale Text and Graph data processingLarge scale Text and Graph data processing
Core Technology• Web crawling
– Nutch + plugins
• Full text indexing and search– lucene, Sorl
• Information Extraction– Ontea, GATE
• All above large scale– Hadoop, S4
• Graph processing and Querying– Simple Graph Database (SGDB)
– gSemSearch
– Neo4j
– Blueprints
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Underlined are the technologies developed by IISAS
Ontea: Information Extraction ToolOntea: Information Extraction Tool
Regex patternsGazetteersResuls
Key-value pairs Structured into trees graphs
Transformers, ConfigurationAutomatic loading of extractors
Visual Annotation Tool Integration with external tools
GATE, Stemers, Hadoop …Multilingual tests
English, Slovak, Spanish, Italian
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http://ontea.sf.net
• Use of Social Network from email• Includes extracted objects• Full text of extracted objects• Related objects discovered and
ordered by spread activation on social network graph
• Faceted search, navigation
Email Search PrototypeEmail Search Prototype
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gSemSearch: Graph based Semantic SearchgSemSearch: Graph based Semantic Search
• Graph/Network of interacting (interconnected) entities• Discovering relation in the Graph (network) using spread of activation algorithm• Showing relations of concrete type, e.g. telephone numbers related to a person• Navigation over related entities• Full-text search of the entities• User interface for search• User interaction with data (merging,
deleting entities) with immediate impact on discovered relations
• Tested on Email Enron Corpus– Email Social Network Search– http://ikt.ui.sav.sk/esns/
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SGDB: Simple Graph DatabaseSGDB: Simple Graph Database
• Storage for graphs• Optimized for graph traversing and spread of activation• Faster then Neo4j for graph traversing operations• Supports Blueprints API• https://simplegdb.svn.sourceforge.net/svnroot/simplegdb/Sgdb3
• Graph Database Benchmarks– Graph Traversal Benchmark for Graph Databases
– http://ups.savba.sk/~marek/gbench.html
– Blueprints API - possibility to test compliant Graph databases
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Future Direction: Relations Discovery in Large Graph DataFuture Direction: Relations Discovery in Large Graph Data
• Motivation– Graph/Network data are everywhere: social networks, web, LinkedData,
transactions, communication (email, phone). – Also text can be converted to graph. – Interconnecting graph data and searching for relations is crucial.
• Approach– Forming semantic trees and graphs from text, web, communication, databases
and LinkedData– User interaction with graph data in order to achieve integration and data
cleansing– Users will do it, if user effort have immediate impact on search results
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