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2008
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A general optimization framework for smoothing language models on graph structures

10 years 4 months ago
A general optimization framework for smoothing language models on graph structures
Recent work on language models for information retrieval has shown that smoothing language models is crucial for achieving good retrieval performance. Many different effective smoothing methods have been proposed, which mostly implement various heuristics to exploit corpus structures. In this paper, we propose a general and unified optimization framework for smoothing language models on graph structures. This framework not only provides a unified formulation of the existing smoothing heuristics, but also serves as a road map for systematically exploring smoothing methods for language models. We follow this road map and derive several different instantiations of the framework. Some of the instantiations lead to novel smoothing methods. Empirical results show that all such instantiations are effective with some outperforming the state of the art smoothing methods. Categories and Subject Descriptors: H.3.3 [Information Search and Retrieval]: Retrieval Models General Terms: Algorithms
Qiaozhu Mei, Duo Zhang, ChengXiang Zhai
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where SIGIR
Authors Qiaozhu Mei, Duo Zhang, ChengXiang Zhai
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