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New Technology of Library and Information Service  2008, Vol. 24 Issue (9): 41-46    DOI: 10.11925/infotech.1003-3513.2008.09.07
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Analysis of Lexical Cohesion Based on HowNet
Shi JingDai Guozhong 2
1(College of Computer Science and Engineering, Changchun University of Technology,Changchun 130021, China)
2(Institute of Software, Chinese Academy of Sciences, Beijing 100190,China)
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Abstract  

Lexical  cohesion provides an indicator of text structure and therefore, it has been used in many natural language process applications. The paper gives an approach of analyzing lexical cohesion based on HowNet. The knowledge of HowNet is represented in semantic network firstly. And then semantic paths are constructed heuristically between concepts of semantic networks  by inference. Lexical chains which express lexical cohesion are found based on semantic paths finally. The results of tests show that the lexical chains got by the introduced method are basically in accord with human’s intuition and the precision is reasonable.

Key words Lexical cohesion      Semantic Network      Text inference     
Received: 17 June 2008      Published: 25 September 2008
: 

TP391

 
Corresponding Authors: Shi Jing     E-mail: crystal1087@126.com
About author:: Shi Jing,Dai Guozhong

Cite this article:

Shi Jing,Dai Guozhong. Analysis of Lexical Cohesion Based on HowNet. New Technology of Library and Information Service, 2008, 24(9): 41-46.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2008.09.07     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2008/V24/I9/41

[1] Ellman J, Emery G. UNN-WePS: Web Person Search Using co-Present Names and Lexical Chains[C]. In: Proceedings of the Fourth International Workshop on Semantic Evaluations,2007.
[2] Balduccini M, Baral C, and Lierler Y. Knowledge Representation and Question Answering, Chapter 20. Handbook of Knowledge Representation[M]. USA:Elsevier, 2007.
[3] Chen Y M,Liu B Q, Wang X L.Automatic Text Summarization Based on Textual Cohesion[J]. Journal of Electronics (China).2007,24(3):338-346.
[4] Stokes N, Carthy J, Smeaton A F. SeLeCT: A Lexical Cohesion based News Story Segmentation System[J]. Journal of AI Communications, 2004,17(1): 3-12.
[5] 石晶.中文文本的主题分析技术研究[D].北京:中国科学院软件研究所.2007.
[6] Morris J, Graeme H. Lexical Cohesion Computed by Thesaural Relations as an Indicator of the Structure of Text[J]. Computational Linguistics,1991,17(1): 21-48.
[7] Harabagiu S M. WordNet-Based Inference of Textual Cohesion and Coherence[C]. In: Proceedings of Eleventh International Florida Artificial Intelligence Research Society Conference, Sanibel Island, FL. 1998: 265-269.
[8] 石晶,戴国忠.基于知网的文本推理[J].中文信息学报,2006, 20(1):76-84.

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