Title: | smoothing document language model with local word graph |
Author: | Huang Yunping
; Sun Le
; Nie Jian-Yun
|
Source: | International Conference on Information and Knowledge Management, Proceedings
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Conference Name: | ACM 18th International Conference on Information and Knowledge Management, CIKM 2009
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Conference Date: | 40849
|
Issued Date: | 2009
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Conference Place: | Hong Kong, China
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Keyword: | Computational linguistics
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Publisher: | United States
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Publish Place: | United States
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Indexed Type: | 其他
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ISBN: | 9781605585123
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Department: | (1) Institute of Software, Chinese Academy of Sciences, Beijing, China; (2) Department of Computer Science and Operations Research, University of Montreal, Canada
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Sponsorship: | ACM SIGIR; ACM SIGWEB
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English Abstract: | Smoothing document model with word graph is a new and effective method in information retrieval. Word graph can naturally incorporate the dependency between the words; random walk algorithm based on the graph can be used to estimate the weight of each vertex. In this paper, we present a new way to construct a local word graph for smoothing document model, which exploits the documents k nearest neighbors: the vertices represent the words in the document and its k nearest neighbors, and the weights of the edges are estimated through word co-occurrence in the local document set. We argue that word graph is a key factor to the performance in graph-based smoothing method. By using the local document set, we can obtain a document specific word graph, and achieve better retrieval performance. Experimental results on three TREC collections show that our proposed approach is effective. Copyright 2009 ACM. |
Language: | 英语
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Content Type: | 会议论文
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URI: | http://ir.iscas.ac.cn/handle/311060/8446
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Appears in Collections: | 基础软件国家工程研究中心_会议论文
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smoothing document language model with local word graph.pdf(488KB) | -- | -- | 限制开放 | -- | 联系获取全文 |
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Recommended Citation: |
Huang Yunping,Sun Le,Nie Jian-Yun. smoothing document language model with local word graph[C]. 见:ACM 18th International Conference on Information and Knowledge Management, CIKM 2009. Hong Kong, China. 40849.
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