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Inferring Users’ Interest on Web Documents Through Their Implicit Behaviour

  • Stephen AkumaEmail author
  • Chrisina Jayne
  • Rahat Iqbal
  • Faiyaz Doctor
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 517)

Abstract

This paper examines the correlation of implicit and explicit user behaviour indicators in a task specific domain. An experiment was conducted and data was collected from 77 undergraduate students of Computer science. Users’ implicit features and explicit ratings of document relevance were captured and logged through a plugin in Firefox browser. A number of implicit indicators were correlated with user explicit ratings and a predictive function model was derived. Classification algorithms were also used to classify documents according to how relevant they are to the current task. It was found that implicit indicators could be used successfully to predict the user rating. These findings can be utilised in building individual and group profile for users of a context-based recommender system.

Keywords

Implicit indicators Explicit rating Context based Recommender system 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Stephen Akuma
    • 1
    Email author
  • Chrisina Jayne
    • 1
  • Rahat Iqbal
    • 1
  • Faiyaz Doctor
    • 1
  1. 1.Department of Computing and the Digital EnvironmentCoventry UniversityCoventryUK

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