Abstract
This paper presents a multi-dependency language modeling approach to information retrieval. The approach extends the basic KL-divergence retrieval approach by introducing the hybrid dependency structure, which includes syntactic dependency, syntactic proximity dependency and co-occurrence dependency, to describe dependencies between terms. Term and dependency language models are constructed for both document and query. The relevant between a document and a query is then evaluated by using the KL-divergence between their corresponding models. The new dependency retrieval model has been compared with other traditional retrieval models. Experiment results indicate that it produces significant improvements in retrieval effectiveness.
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Cai, K., Chen, C., Bu, J., Qiu, G., Huang, P. (2007). A Multi-dependency Language Modeling Approach to Information Retrieval. In: Washio, T., et al. Emerging Technologies in Knowledge Discovery and Data Mining. PAKDD 2007. Lecture Notes in Computer Science(), vol 4819. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77018-3_48
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DOI: https://doi.org/10.1007/978-3-540-77018-3_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77016-9
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