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

, , and . WI '07: Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, page 683--686. Washington, DC, USA, IEEE Computer Society, (2007)
DOI: http://dx.doi.org/10.1109/WI.2007.137

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.

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

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