Graph Pattern Index for Neo4j Graph Databases
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10395844" target="_blank" >RIV/00216208:11320/19:10395844 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-26636-3_4" target="_blank" >http://dx.doi.org/10.1007/978-3-030-26636-3_4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-26636-3_4" target="_blank" >10.1007/978-3-030-26636-3_4</a>
Alternative languages
Result language
angličtina
Original language name
Graph Pattern Index for Neo4j Graph Databases
Original language description
Nowadays graphs have become very popular in domains like social media analytics, healthcare, natural sciences, BI, networking, etc. Graph databases (GDB) allow simple and rapid retrieval of complex graph structures that are difficult to model in traditional information systems based on a relational DBMS. GDB are designed to exploit relationships in data, which means they can uncover patterns difficult to detect using traditional methods. We introduce a new method for indexing graph patterns within a GDB modelled as a labelled property graph. The index is based on so called graph pattern trees of variations and stored in the same database where the database graph. The method is implemented for Neo4j GDB engine and analysed on three graph datasets. It enables to create, use and update indexes that are used to speed-up the process of matching graph patterns. The paper provides details of the implementation, experiments, and a comparison between queries with and without using indexes.
Czech name
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Czech description
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Classification
Type
C - Chapter in a specialist book
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
Data Management Technologies and Applications. DATA 2018.
ISBN
978-3-030-26635-6
Number of pages of the result
22
Pages from-to
69-90
Number of pages of the book
210
Publisher name
Springer
Place of publication
Neuveden
UT code for WoS chapter
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