Abstract
Query similarity computation is one of important factors in the process of query clustering. It has been used widely in the field of information processing. In this paper, a unified model for query similarity computation is presented based on system similarity. The novel approach of similarity computation uses the literal, semantic and statistical relative features of query. The method can take advantage of the normal approaches to improve the computation accuracy. Experiments show that the proposed method is an effective solution to the query similarity computation problem, and it can be generalized to measure the similarity of other components of text, such as sentences, paragraphs etc.
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Zhang, C., Xu, X., Su, X. (2006). Query Similarity Computing Based on System Similarity Measurement. In: Matsumoto, Y., Sproat, R.W., Wong, KF., Zhang, M. (eds) Computer Processing of Oriental Languages. Beyond the Orient: The Research Challenges Ahead. ICCPOL 2006. Lecture Notes in Computer Science(), vol 4285. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11940098_5
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DOI: https://doi.org/10.1007/11940098_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49667-0
Online ISBN: 978-3-540-49668-7
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