Full-text Support for Publish/Subscribe Ontology Systems

TL;DR

This paper introduces a novel publish/subscribe ontology system with full-text support, enabling efficient indexing and filtering of millions of subscriptions against streaming ontology data using an extended SPARQL language.

Contribution

It proposes a SPARQL extension for full-text subscriptions and a main-memory indexing algorithm for fast semantic and full-text matching in publish/subscribe systems.

Findings

Supports indexing millions of subscriptions efficiently

Achieves low-latency filtering and matching

Enables real-time notifications for streaming data

Abstract

We envision a publish/subscribe ontology system that is able to index millions of user subscriptions and filter them against ontology data that arrive in a streaming fashion. In this work, we propose a SPARQL extension appropriate for a publish/subscribe setting; our extension builds on the natural semantic graph matching of the language and supports the creation of full-text subscriptions. Subsequently, we propose a main-memory subscription indexing algorithm which performs both semantic and full-text matching at low complexity and minimal filtering time. Thus, when ontology data are published matching subscriptions are identified and notifications are forwarded to users.