Creating Triggers with Trigger-By-Example in Graph Databases

Rabuzin, Kornelije; Šestak, Martina

doi:10.5220/0007829601370144

Cited by 3 publications

(3 citation statements)

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“…Specifikacija okidača u grafovskoj bazi Na primjeru se može vidjeti kako nije moguće dodati novi čvor Job Posting ako već ne postoji čvor Agency sa svojstvom name = NYC HOUSING AUTHORITY. Više informacija o implementaciji može se pronaći u (Rabuzin & Šestak, 2019).…”

Section: Okidačiunclassified

Istraživanja u području grafovskih baza podataka

Rabuzin

Kudelić

2020

Politehnika (Online)

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Kako smo unatrag nekoliko godina dobili određena sredstva (tzv. sveučilišne potpore) kojima smo istraživali određene aspekte grafovskih baza podataka, odlučili smo rezultate istraživanja predstaviti i hrvatskoj akademskoj i stručnoj zajednici. Smatramo kako su istraživanja bila kvalitetna i da rezultati istih imaju potencijal za širu primjenu i implementaciju u dostupnim sustavima za upravljanje grafovskim bazama podataka. Također, postoje i određene mogućnosti za proširenje implementiranih rješenja, kao i prostor za dodatna istraživanja i preslikavanja relacijskih u koncepte grafovskih baza podataka

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Section: Okidačiunclassified

Istraživanja u području grafovskih baza podataka

Rabuzin

Kudelić

2020

Politehnika (Online)

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“…There is limited research on incorporating fuzzy logic or active rules into graph databases. The research in [8] described the approach of "Trigger-By-Example" to implement triggers in graph databases, including both BEFORE INSERT trigger and AFTER INSERT trigger. This approach is a variation of the traditional Query-By-Example approach.…”

Section: Related Workmentioning

confidence: 99%

“…It also has a continuous query processor to save the subgraph-action rules to perform specified actions. Both [8] and [9] only allow users to specify the rules containing crisp values. The research in [10] added fuzzy logic to Neo4j, which defined "fuzzy data" as a new data type.…”

Section: Related Workmentioning

confidence: 99%

Mutation Event and Fuzzy Active Rule Processing in a Graph Database System

Jin¹,

Shah²

EPiC Series in Computing

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A graph database system is a type of NoSQL databases that is based on the graph data model using nodes and arcs. Existing graph databases are passive and can only handle crisp data. Information in the real world can be imprecise and vague rather than crisp. Integrating fuzzy logic into database systems allows users to use uncertain data, which presents the degree to which something is true. Compared with passive databases, active databases support event handling by monitoring and reacting to specific circumstances automatically. This paper describes our approach of incorporating fuzzy concepts and active rules into a graph database system. Our recent publication has described our work of temporal event processing. This paper focuses on mutation events handling and active rule processing in a fuzzy system, covering the language model, the execution model, and architecture design. The language model defines the rule structure and contains the metadata for rule processing. Architecture design identifies the system's architectural components and user interfaces including rule specification interface and query interface. The execution model handles rule processing and execution at run time. A supply chain application is used to demonstrate the examples of active rule specification and execution.

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Extending Graph Databases With Relational Concepts

Rabuzin

Čubrilo

Šestak

2022

Encyclopedia of Data Science and Machine Learning

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Today we have to deal with large amounts of data, and for large amounts of interconnected data, graph databases represent an excellent choice. However, some concepts that are used in relational databases are still not supported in graph databases, and this could hinder their wider use. In this article, how relational database concepts have been successfully transferred into graph databases, including integrity constraint support, inheritance, trigger specification, new visual query languages, etc., is demonstrated.

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Creating Triggers with Trigger-By-Example in Graph Databases

Cited by 3 publications

References 0 publications

Istraživanja u području grafovskih baza podataka

Istraživanja u području grafovskih baza podataka

Mutation Event and Fuzzy Active Rule Processing in a Graph Database System

Extending Graph Databases With Relational Concepts

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