Abstract
Understanding user goal has played an important role in improving the quality of the search engines. Many previous researches focus on finding prominent statistical features to classify the user goal into Border’s taxonomy. But it is difficult to achieve high precision because of the weakness of taxonomy definition. This paper first gives a lexicalized taxonomy for user goal, and then proposes a dependency relation based algorithm to detect lexicalized user goals. To alleviate the sparseness of direct dependency relation, we extend our algorithm to include second order dependency relations. The experimental results show that our extended algorithm can achieve precision of 89% on correctness and 79% on relevance, and thus it outperforms previous related algorithm significantly.
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Duan, R., Wang, X., Hu, R., Tian, J. (2010). Dependency Relation Based Detection of Lexicalized User Goals. In: Yu, Z., Liscano, R., Chen, G., Zhang, D., Zhou, X. (eds) Ubiquitous Intelligence and Computing. UIC 2010. Lecture Notes in Computer Science, vol 6406. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16355-5_15
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DOI: https://doi.org/10.1007/978-3-642-16355-5_15
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