@inproceedings{zhang-wang-2017-noise,
title = "Noise-Clustered Distant Supervision for Relation Extraction: A Nonparametric {B}ayesian Perspective",
author = "Zhang, Qing and
Wang, Houfeng",
editor = "Palmer, Martha and
Hwa, Rebecca and
Riedel, Sebastian",
booktitle = "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing",
month = sep,
year = "2017",
address = "Copenhagen, Denmark",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D17-1192",
doi = "10.18653/v1/D17-1192",
pages = "1808--1813",
abstract = "For the task of relation extraction, distant supervision is an efficient approach to generate labeled data by aligning knowledge base with free texts. The essence of it is a challenging incomplete multi-label classification problem with sparse and noisy features. To address the challenge, this work presents a novel nonparametric Bayesian formulation for the task. Experiment results show substantially higher top precision improvements over the traditional state-of-the-art approaches.",
}
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%0 Conference Proceedings
%T Noise-Clustered Distant Supervision for Relation Extraction: A Nonparametric Bayesian Perspective
%A Zhang, Qing
%A Wang, Houfeng
%Y Palmer, Martha
%Y Hwa, Rebecca
%Y Riedel, Sebastian
%S Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F zhang-wang-2017-noise
%X For the task of relation extraction, distant supervision is an efficient approach to generate labeled data by aligning knowledge base with free texts. The essence of it is a challenging incomplete multi-label classification problem with sparse and noisy features. To address the challenge, this work presents a novel nonparametric Bayesian formulation for the task. Experiment results show substantially higher top precision improvements over the traditional state-of-the-art approaches.
%R 10.18653/v1/D17-1192
%U https://aclanthology.org/D17-1192
%U https://doi.org/10.18653/v1/D17-1192
%P 1808-1813
Markdown (Informal)
[Noise-Clustered Distant Supervision for Relation Extraction: A Nonparametric Bayesian Perspective](https://aclanthology.org/D17-1192) (Zhang & Wang, EMNLP 2017)
ACL