Pattern Matching Over Linked Data Streams

Yongrui Qin, Quan Z. Sheng

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


This chapter leverages semantic technologies, such as Linked Data,which can facilitate machine-to-machine (M2M) communications to build an efficient information dissemination system for semantic IoT. The system integrates Linked Data streams generated from various data collectors and disseminates matched data to relevant data consumers based on triple pattern queries registered in the system by the consumers. We also design two new data structures, TP-automata and CTPautomata, to meet the high performance needs of Linked Data dissemination. We evaluate our system using a real-world dataset generated from a Smart Building Project. With the new data structures, the proposed system can disseminate Linked Data faster than the existing approach with thousands of registered queries.

Original languageEnglish
Title of host publicationHandbook of Big Data Technologies
PublisherSpringer International Publishing AG
Number of pages19
ISBN (Electronic)9783319493404
ISBN (Print)9783319493398
Publication statusPublished - 25 Feb 2017


Dive into the research topics of 'Pattern Matching Over Linked Data Streams'. Together they form a unique fingerprint.

Cite this