Unsupervised Learning of Dependency Structure for Language Modeling (2003)
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Jianfeng Gao Microsoft
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Jianfeng Gao
| Venue: | In ACL |
BibTeX
@INPROCEEDINGS{Microsoft03unsupervisedlearning,
author = {Jianfeng Gao Microsoft and Jianfeng Gao},
title = {Unsupervised Learning of Dependency Structure for Language Modeling},
booktitle = {In ACL},
year = {2003},
pages = {521--528}
}
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Abstract
This paper presents a dependency language model (DLM) that captures linguistic constraints via a dependency structure, i.e., a set of probabilistic dependencies that express the relations between headwords of each phrase in a sentence by an acyclic, planar, undirected graph. Our contributions are three-fold. First, we incorporate the dependency structure into an n-gram language model to capture long distance word dependency.
Citations
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