Request Dependency Graph: A Model for Web Usage Mining in Large-Scale Web of Things

Jun Liu, Cheng Fang, Nirwan Ansari

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


In the Web of Things (WoT) environment, Web traffic logs contain valuable information of how people interact with smart devices and Web servers. Mining the wealth of information available in the Web access logs has theoretical and practical significance for many important applications like network optimization and security management. The first critical step of the mining task is modeling the relationships among HyperText Transfer Protocol (HTTP) requests for accessing Web objects to investigate the behavior of Web clients. In this paper, we introduce the request dependency graph (RDG), a graph representation of the relationships among HTTP requests. Conceptually, a directed link from A to B in the graph means that the accessing of Web object B is caused by the accessing of A, i.e., B depends on A. We propose a methodology to establish such a graph by mining the temporal and causal information among aggregated HTTP requests. To demonstrate the value and effectiveness of the proposed model, we design and implement an algorithm for primary requests identification, which is a critical task of Web usage mining, based on the RDG. Evaluation results from a large-scale real-world Web access log shows that the RDG is a useful tool for Web usage mining.

Original languageEnglish (US)
Article number7150334
Pages (from-to)598-608
Number of pages11
JournalIEEE Internet of Things Journal
Issue number4
StatePublished - Aug 2016

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications


  • Graph model
  • HTTP traffic
  • Web data mining
  • Web of Things (WoT)
  • Web usage mining
  • request dependency graph (RDG)


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