Improving Identification of Latent User Goals through Search-Result Snippet Classification

  • Authors:
  • Kuan-Yu He;Yao-Sheng Chang;Wen-Hsiang Lu

  • Affiliations:
  • -;-;-

  • Venue:
  • WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
  • Year:
  • 2007

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Abstract

In this paper, we propose an enhanced approach to improving our previous method which employs syntactic structures (verb-object pairs) to identify latent user goals. Our new approach employs a supervised-learning method to learn hint verbs and considers URL information and title information to classify snippets into three coarse categories, which are resource-seeking, informational, and navigational. Also, we propose three different models to identify three different categories of specific latent user goals from the classified snippets.