Structuring ordered nominal data for event sequence discovery

  • Authors:
  • Chreston A. Miller;Francis Quek;Naren Ramakrishnan

  • Affiliations:
  • Virginia Tech, Blacksburg, VA, USA;Virginia Tech, Blacksburg, VA, USA;Virginia Tech, Blacksburg, VA, USA

  • Venue:
  • Proceedings of the international conference on Multimedia
  • Year:
  • 2010

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Abstract

This work investigates using n-gram processing and a temporal relation encoding to providing relational information about events extracted from media streams. The event information is temporal and nominal in nature being categorized by a descriptive label or symbolic means and can be difficult to relationally compare and give ranking metrics. Given a parsed sequence of events, relational information pertinent to comparison between events can be obtained through the application of n-grams techniques borrowed from speech processing and temporal relation logic. The procedure is discussed along with results computed using a representative data set characterized by nominal event data.