Pattern Matching Over Linked Data Streams

Yongrui Qin, Quan Z. Sheng

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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
Pages409-427
Number of pages19
ISBN (Electronic)9783319493404
ISBN (Print)9783319493398
DOIs
Publication statusPublished - 25 Feb 2017

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    Qin, Y., & Sheng, Q. Z. (2017). Pattern Matching Over Linked Data Streams. In Handbook of Big Data Technologies (pp. 409-427). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-49340-4_12