English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The property graph data model of modern graph database systems isincreasingly adapted for storing and processing heterogeneous datasets likenetworks. Many challenging applications with near real-time requirements --e.g. financial fraud detection, recommendation systems, and on-the-flyvalidation -- can be captured with graph queries, which are evaluatedrepeatedly. To ensure quick response time for a changing data set, theseapplications would benefit from applying incremental view maintenance (IVM)techniques, which can perform continuous evaluation of queries and calculatethe changes in the result set upon updates. However, currently, no graphdatabases provide support for incremental views. While IVM problems have beenstudied extensively over relational databases, views on property graph queriesrequire operators outside the scope of standard relational algebra. Hence,tackling this problem requires the integration of numerous existing IVMtechniques and possibly further extensions. In this paper, we present anapproach to perform IVM on property graphs, using a nested relational algebraicrepresentation for property graphs and graph operations. Then we define a chainof transformations to reduce most property graph queries to flat relationalalgebra and use techniques from discrimination networks (used in rule-basedexpert systems) to evaluate them. We demonstrate the approach using ourprototype tool, ingraph, which uses openCypher, an open graph query languagespecified as part of an industry initiative. However, several aspects of ourapproach can be generalised to other graph query languages such as G-CORE andPGQL.

Reducing Property Graph Queries to Relational Algebra for Incremental View Maintenance