Abstract
To best exploit the context information for meaningful hints to the user’s intent, this paper proposes an adaptive weighting approach to improve the current context-sensitive retrieval model. The potential for adaptability is first investigated as the performance gap between the current context-sensitive models with a fixed form weight and those with adaptive weights for contextual information. Then the proper context weight is predicated according to the relation strength between the query and its context. The experimental results on a public available dataset indicate that the proposed approach outperforms three baseline methods.
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Wang, X., Yang, M., Qi, H., Li, S., Zhao, T. (2012). Adaptive Weighting Approach to Context-Sensitive Retrieval Model. In: Hou, Y., Nie, JY., Sun, L., Wang, B., Zhang, P. (eds) Information Retrieval Technology. AIRS 2012. Lecture Notes in Computer Science, vol 7675. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35341-3_37
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DOI: https://doi.org/10.1007/978-3-642-35341-3_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35340-6
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