| 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
|
| Conference Name: | ACM 18th International Conference on Information and Knowledge Management, CIKM 2009
|
| Conference Date: | 40849
|
| Issued Date: | 2009
|
| Conference Place: | Hong Kong, China
|
| Keyword: | Computational linguistics
|
| Publisher: | United States
|
| Publish Place: | United States
|
| Indexed Type: | 其他
|
| ISBN: | 9781605585123
|
| Department: | (1) Institute of Software, Chinese Academy of Sciences, Beijing, China; (2) Department of Computer Science and Operations Research, University of Montreal, Canada
|
| Sponsorship: | ACM SIGIR; ACM SIGWEB
|
| 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
|
| Content Type: | 会议论文
|
| URI: | http://ir.iscas.ac.cn/handle/311060/8446
|
| 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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