Micro-blogs Entity Recognition Based on DSTCRF

WANG Jing; LIU Zhijing; ZHAO Hui

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Article Navigation > Chinese Journal of Electronics > 2014 > 23(1): 147-150

WANG Jing, LIU Zhijing, ZHAO Hui, “Micro-blogs Entity Recognition Based on DSTCRF,” Chinese Journal of Electronics, vol. 23, no. 1, pp. 147-150, 2014,

Citation:

WANG Jing, LIU Zhijing, ZHAO Hui, “Micro-blogs Entity Recognition Based on DSTCRF,” Chinese Journal of Electronics, vol. 23, no. 1, pp. 147-150, 2014,

WANG Jing, LIU Zhijing, ZHAO Hui, “Micro-blogs Entity Recognition Based on DSTCRF,” Chinese Journal of Electronics, vol. 23, no. 1, pp. 147-150, 2014,

Citation:

WANG Jing, LIU Zhijing, ZHAO Hui, “Micro-blogs Entity Recognition Based on DSTCRF,” Chinese Journal of Electronics, vol. 23, no. 1, pp. 147-150, 2014,

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Micro-blogs Entity Recognition Based on DSTCRF

1.
Xidian University, Xi'an 710071, China;
2.
Xi'an Jiaotong University, Xi'an 710049, China

Funds: This work is supported by the National Natural Science Foundation of China (No.61173091, No.61202177).

Received Date: 2013-01-01
Rev Recd Date: 2013-04-01
Publish Date: 2014-01-05

Abstract

Abstract

We proposed a unified model for Chinese named entity recognition in micro-blogs. The models provide a simple statistical framework to incorporate a wide variety of linguistic knowledge and statistical models in a unified way. In our approach, KNN classifier is used to get suitable training data. An optimal algorithm to generate the hierarchically structured DSTCRF is executed to select the structure attributes of the named entity in micro-blogs knowledge. The experimental results showed that the accuracy rate was significantly improved.
- Named entity,
- Micro-blog,
- Probability model

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References(10)

References

A. Ritter, S. Clark, Mausam and O. Etzioni,"Named entity recognition in tweets: An experimental study", Proc. of Conference on Empirical Methods in Natural Language Processing, Edinburgh, Scotland, UK, pp.1524-1534, 2011.

J.S. Zhou, W.G. Qu, F. Zhang,"Chinese named entity recognition via joint identification and categorization", Chinese Journal of Electronics, Vol.22, No.2, pp.225-230, 2013.

D. Wu, W.S. Lee, N. Ye and H.L. Chieu,"Domain adaptive bootstrapping for named entity recognition", Proc. of 2009 Conference on Empirical Methods in Natural Language Processing, Singapore, pp.1523-1532, 2009.

L. Chiticariu, R. Krishnamurthy, Y.Y. Li, et al.,"Domain adaptation of rule-based annotators for na al, med-entity recognition tasks", Proc. of 2010 Conference on Empirical Methods in Natural Language Processing, MIT, Massachusetts, USA, pp.10021012, 2010.

C.L. Li, J.S. Weng, Q. He, et al.,"TwiNER: Named entity recognition in targeted twitter stream", Proc. of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, Portland, Oregon, USA, pp.721-730, 2012.

C. Wang, K. Chakrabarti, T. Cheng, et al.,"Targeted disambiguation of Ad-hoc, homogeneous sets of named entities", Proc. of the 21st international conference on World Wide Web, Lyon, France, pp.719-728, 2012.

V.T. Chakaravarthy, V. Pandit, S. Roy, et al.,"Decision trees for entity identification: Approximation algorithms and hardness results", Proc. of the twenty-sixth ACM SIGMODSIGACTSIGART Symposium on Principles of Database Systems, Beijing, China, pp.53-62, 2007.

X. Liu, S. Zhang, F. Wei and M. Zhou,"Recognizing named entities in tweets", Proc. of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Portland, Oregon, USA, pp.359-367, 2011.

Y. Merhav, F. Mesquita, D. Barbosa, et al.,"Incorporating global information into named entity recognition systems using relational context", Proc. of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, Geneva, Switzerland, pp.883-884, 2010.

T.T. Truyen, D.Q. Phung, H.H. Bui, et al.,"Hierarchical semiMarkov conditional random fields for recursive sequential data", Proc. of Twenty-Second Annual Conference on Neural Information Processing Systems, Vancouver, Canada, pp.1185-1192, 2004.

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