Building Entity Graphs for the Web of Things Management

Lina Yao*, Quan Z. Sheng, Anne H.H. Ngu, Xue Li, Boualem Benatallah, Xianzhi Wang

*Corresponding author for this work

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


With recent advances in radio-frequency identification (RFID), wireless sensor networks, and Web services, physical things are becoming an integral part of the emerging ubiquitous Web. Finding correlations among ubiquitous things is a crucial prerequisite for many important applications such as things search, discovery, classification, recommendation, and composition. This article building an entity graph for Web of Things, whereas we propose a novel graph-based approach for discovering underlying connections of things via mining the rich content embodied in the human-thing interactions in terms of user, temporal and spatial information. We model this various information using two graphs, namely a spatiotemporal graph and a social graph. Then, random walk with restart (RWR) is applied to find proximities among things, a relational graph of things, entity graph, indicating implicit correlations of things is learned. The correlation analysis lays a solid foundation contributing to improved effectiveness in things management and analytics. To demonstrate the utility of the proposed approach, we present two typical applications and a systematic case study in regards to a flexible feature-based classification framework and a unified probabilistic factor based framework, respectively. Our evaluation exhibits the strength and feasibility of approach.

Original languageEnglish
Title of host publicationManaging the Web of Things
Subtitle of host publicationlinking the real world to the web
EditorsQuan Z. Sheng, Yongrui Qin, Lina Yao, Boualem Benatallah
Place of PublicationCambridge, MA
PublisherMorgan Kaufmann Publishers
Number of pages29
ISBN (Electronic)9780128097656
ISBN (Print)9780128097649
Publication statusPublished - 8 Feb 2017


  • Classification
  • Correlation discovery
  • Internet of things
  • Matrix factorization
  • Random walk with restart
  • Recommendation


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