Context-aware content filtering & presentation for pervasive & mobile information systems

  • Authors:
  • Kaijian Xu;Manli Zhu;Daqing Zhang;Tao Gu

  • Affiliations:
  • Nanyang Technological University, Singapore;Institute for Infocomm Research, Singapore;GET/INT Institut National des Télécommunications, Evry Cedex, France;Institute for Infocomm Research, Singapore

  • Venue:
  • Proceedings of the 1st international conference on Ambient media and systems
  • Year:
  • 2008

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Abstract

What constitutes relevant information to an individual may vary widely under different contexts. However, previous work on pervasive information systems has mostly focused on context-aware delivery of application-specific information. Such systems are only able to operate within narrow application domains and cannot be generalized to handle other heterogeneous types of information. To fill this gap, we propose a context-aware system for information integration that can handle arbitrary information types and determine their relevance to the user's current context. In contrast to existing model-based approaches to context reasoning, we log user interaction and perform usage mining using OLAP to discover context-dependent preferences for different information types. This allows us to build a more generic and adaptive system that automatically selects the most relevant content and presents it to the user in a succinct manner that supports ease of consumption and comprehension.