Keywords Extraction Based on Text Classification

Li Gong Yang; Jian Zhu; Shi Ping Tang

doi:10.4028/www.scientific.net/AMR.765-767.1604

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 765-767Keywords Extraction Based on Text Classification

Keywords Extraction Based on Text Classification

Abstract:

In this paper, we propose new keywords extraction method based on texts classification. We first classify texts to determine their categories. Then determine weights of candidate words according to both their frequency and the relevance between text words and text category. Finally, keywords are extracted by sorting weights of candidate words. We conduct this experiment to show that on the premise of accurate text classification, this method can extract keywords effectively from text without title or with deviated title which can not reflect texts subject. Objective selecting of candidate word weighting function still needs to be further researched.

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Periodical:

Advanced Materials Research (Volumes 765-767)

Pages:

1604-1609

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.765-767.1604

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Online since:

September 2013

Authors:

Li Gong Yang, Jian Zhu, Shi Ping Tang

Keywords:

Candidate Word, Keyword Extraction, Text Classification, Weight Function CLC Number: TP391.1

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References

[1] Brook Wu Yi-fang, Li Quan-zhi, Razvan Stefan Bot, et a1. KIP: a keyphrase identification program with learning functions[C]. Proceedings of the International Conference on Information Technology: Coding and Computing(ITCC'04), (2004).

DOI: 10.1109/itcc.2004.1286694

Google Scholar

[2] Hulth A. Improved automatic keyword extraction given more linguistic knowledge[C]. Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing, 2003: 216-223.

DOI: 10.3115/1119355.1119383

Google Scholar

[3] Tumey P. Learning to extract key phrases from text, NRC／ERB－1057[R], 1999, 02, 17.

Google Scholar

[4] Yang Wen-Feng. Chinese keyword extraction based on max2dup licated strings of the documents[A ]. In: Proceedings of the 25 th Annual InternationalACM SIGIR Conference on Research and Development in Information Retrieval[C ] , Tampere, Finland, 2002: 439 - 440.

DOI: 10.1145/564376.564483

Google Scholar

[5] ZHENG Jia-heng, LU Jiaoli . Study of An Improved Keywords Distillation Method[J]. Computer Engineering , 2005, 31(18): 194－196 (in Chinese).

Google Scholar

[6] LIU Jia-bin, CHEN Chao, SHAO Zheng-rong et al. Automatic extraction of key phrases from scientific articles based on machine learning method[J]. Computer Engineering and Application. 2007, 43(14): 170-172(in Chinese).

Google Scholar