A Hybrid Keyword Extraction Method Based on TF and Semantic Strategies for Chinese Document

Su Wang; Ming Ya Wang; Jun Zheng; Kai Zheng

doi:10.4028/www.scientific.net/AMM.635-637.1476

Paper Titles

Research on the Simulation of Tension Control System of the Traction Wire Rope Cleaning and Detection Line of Pay-Off Unit
p.1451

A GPS-Assisted Calibration Algorithm for Misalignment Angle between Star Sensor and Strap-Down Inertial Navigation System
p.1457

A Clustering Algorithm Based on Improved Particle Swarm Optimization
p.1467

A Digital Forensics Method in Cloud Computing Environment
p.1471

A Hybrid Keyword Extraction Method Based on TF and Semantic Strategies for Chinese Document
p.1476

A Modelling Method for Cross-Organizational Business Process Collaboration Based on Petri Net and Process Algebra
p.1480

A New Imputation Method for Treating Missing Precipitation Records
p.1488

A Novel Garment Prototyping Algorithm
p.1496

A Study of RCS Parallel Computing Based on MPI and FDTD
p.1502

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 635-637A Hybrid Keyword Extraction Method Based on TF and...

A Hybrid Keyword Extraction Method Based on TF and Semantic Strategies for Chinese Document

Abstract:

Keyword extraction is important for information retrieval. This paper gave a hybrid keyword extraction method based on TF and semantic strategies for Chinese document. A new word finding method was proposed to find the new word not exist in the dictionary. Moreover the semantic strategies were introduced to filter the dependent words and remove the synonyms. Experimental results show that the proposed method can improve the accuracy and performance of keyword extraction.

You might also be interested in these eBooks

Advanced Design and Manufacturing Technology IV

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 635-637)

Pages:

1476-1479

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.635-637.1476

Citation:

Cite this paper

Online since:

September 2014

Authors:

Su Wang*, Ming Ya Wang, Jun Zheng, Kai Zheng

Keywords:

Chinese Document, Frequency, Keyword Extraction, New Word, Synonym

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Li Juanzi, Fan Qi'na, Zhang Kuo. Keyword Extraction Based on tf/idf for Chinese News Document. Wuhan University Journal of Natural Sciences, 2007, 12(5), pp.917-921.

DOI: 10.1007/s11859-007-0038-4

Google Scholar

[2] Liangfang Wang: The Research of Keywords Extraction Algorithm in Text Mining，Zhejiang University of Technology, (2013).

Google Scholar

[3] Liu Qun, Zhang Huaping, YU Hongkui: Chinese Lexical Analysis Using Hierarchical Hidden Markov Model. Chinese Journal of Computer Research and Development, 2004, 41(8), pp.1421-1429.

Google Scholar

[4] Wanxiang Che, Zhenghua Li, Ting Liu: LTP: A Chinese Language Technology Platform. In Proceedings of the Coling 2010: Demonstrations, 2010, pp.13-16.

Google Scholar

[5] Zhan Xuegang, Wu Qiang: Keyword Extraction Algorithm Based On Tf Statistics And Syntactic Parsing. Computer Applications and Software, 2014, 31(1), pp.47-49.

Google Scholar

[6] Chien, L. F.: PAT-Tree-Based Keyword Extraction for Chinese Information Retrieval, Proceedings of the ACM SIGIR International Confer-ence on Information Retrieval, 1997, pp.50-59.

DOI: 10.1145/278459.258534

Google Scholar

[7] Wang Lixia, Huai Xiaoyong: Semantic-based Keyword Extraction Algorithm for Chinese Text. Computer Engineering, 2012, 38(1), pp.1-4.

Google Scholar

[8] Li Sujian, Wang Houfeng, Yu Shiwen, Xin Chengsheng: News-Oriented Automatic Chinese Keyword Indexing. Sighan workshop ACL2003, (2003).

DOI: 10.3115/1119250.1119263

Google Scholar