Ontological analysis of web surf history to maximize the click-through probability of web advertisements

  • Authors:
  • Jason Deane;Praveen Pathak

  • Affiliations:
  • Department of Business Information Technology, Pamplin College of Business, Virginia Tech, Blacksburg, VA 24061, USA;Information Systems and Operations Management Department, Warrington College of Business Administration, University of Florida, Gainesville, FL 32611-7169, USA

  • Venue:
  • Decision Support Systems
  • Year:
  • 2009

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Abstract

Due to an enormous influx of capital over the past decade, the online advertising industry has become extremely robust and competitive. The difference between success and failure in such a competitive market often rests in the ability to deliver advertisements that are closely in line with a user's interests. In this work, we propose and test a new online advertisement targeting technique which adapts and utilizes several powerful and well tested information retrieval and lexical techniques to develop an estimate of a user's affinity for particular products and services based on an analysis of a user's web surfing behavior. This new online ad targeting technique performs extremely well in our empirical tests.