Please wait a minute...
New Technology of Library and Information Service  2006, Vol. 1 Issue (9): 34-37    DOI: 10.11925/infotech.1003-3513.2006.09.08
Current Issue | Archive | Adv Search |
A Text Semantic Information Processing Method Based on Ontology and Latent Semantic Indexing
Qin Chunxiu    Liu Huailiang    Zhao Pengwei
 (School of Economics and Management, Xidian University, Xi’an 710071,China)
Download: PDF(0 KB)   HTML  
Export: BibTeX | EndNote (RIS)      
Abstract  

This paper presents a method for text semantic information processing based on Ontology and latent semantic indexing. Firstly, virtual standard text characteristic vectors are constructed; then, the texts are semantically classified into document sets according to virtual standard text characteristic vectors by using latent semantic indexing method; finally, semantically explicit annotations to the document sets are abtained from Ontology-base by guidance of virtual standard text characteristic vectors. Experiments show that method can achieve good text clustering of semantic level, and the clustering can explicitly indicate categories of the clustered documents.

Key wordsLatent semantic indexing      Ontology      Clustering      Semantics      Annotation     
Received: 20 June 2006      Published: 25 September 2006
: 

G354.2

 
Corresponding Authors: Qin Chunxiu     E-mail: qinchx@126.com
About author:: Qin Chunxiu,Liu Huailiang,Zhao Pengwei

Cite this article:

Qin Chunxiu,Liu Huailiang,Zhao Pengwei . A Text Semantic Information Processing Method Based on Ontology and Latent Semantic Indexing. New Technology of Library and Information Service, 2006, 1(9): 34-37.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2006.09.08     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2006/V1/I9/34

1张晓林.Semantic Web与基于语义的网络信息检索.情报学报,2002,21(4):413-420
2Berry M W, Dumais S T, O. brien G W. Using linear algebra for intelligent information retrieval, SIAM Review, 1995, 37(4):573-595
3Deerwester S, Dumais S T, Furnas G W et al.Indexing by Latent Semantic Analysis, Journal of the American Society for Information Science, 1990, 41(6):391-407
4Neches R, Fikes R E, Gruber T R, et al. Enabling Technology for Knowledge Sharing.AI Magazine, 1991, 12(3):36-56
5W. N. Borst. Construction of Engineering Ontologies for Knowledge Sharing and Reuse. PhD thesis, University of Twente, Enschede, 1997
6林鸿飞,姚天顺.基于潜在语义索引的文本浏览机制.中文信息学报, 2000, 14(5):49-56
7杨梁彬.文本检索的潜在语义索引法初探.大学图书馆学报,2003(6):68-74,84

[1] Zhu Fu,Yuefen Wang,Xuhui Ding. Semantic Representation of Design Process Knowledge Reuse[J]. 数据分析与知识发现, 2019, 3(6): 21-29.
[2] Cheng Zhou,Hongqin Wei. Evaluating and Classifying Patent Values Based on Self-Organizing Maps and Support Vector Machine[J]. 数据分析与知识发现, 2019, 3(5): 117-124.
[3] Quan Lu,Anqi Zhu,Jiyue Zhang,Jing Chen. Research on User Information Requirement in Chinese Network Health Community: Taking Tumor-forum Data of Qiuyi as an Example[J]. 数据分析与知识发现, 2019, 3(4): 22-32.
[4] Jiang Wu,Yinghui Zhao,Jiahui Gao. Research on Weibo Opinion Leaders Identification and Analysis in Medical Public Opinion Incidents[J]. 数据分析与知识发现, 2019, 3(4): 53-62.
[5] Lianjie Xiao,Mengrui Gao,Xinning Su. An Under-sampling Ensemble Classification Algorithm Based on Fuzzy C-Means Clustering for Imbalanced Data[J]. 数据分析与知识发现, 2019, 3(4): 90-96.
[6] Guangshang Gao. A Survey of User Profiles Methods[J]. 数据分析与知识发现, 2019, 3(3): 25-35.
[7] Jiaxin Ye,Huixiang Xiong. Recommending Personalized Contents from Cross-Domain Resources Based on Tags[J]. 数据分析与知识发现, 2019, 3(2): 21-32.
[8] Ying Wang,Li Qian,Jing Xie,Zhijun Chang,Beibei Kong. Building Knowledge Graph with Sci-Tech Big Data[J]. 数据分析与知识发现, 2019, 3(1): 15-26.
[9] Tao Zhang,Haiqun Ma. Clustering Policy Texts Based on LDA Topic Model[J]. 数据分析与知识发现, 2018, 2(9): 59-65.
[10] Xiangdong Li,Fan Gao,Youhai Li. Categorizing Documents Automatically within Common Semantic Space[J]. 数据分析与知识发现, 2018, 2(9): 66-73.
[11] Youshi He,Shufang He. Sentiment Mining of Online Product Reviews Based on Domain Ontology[J]. 数据分析与知识发现, 2018, 2(8): 60-68.
[12] Huihui Tang,Hao Wang,Zixuan Zhang,Xueying Wang. Extracting Names of Historical Events Based on Chinese Character Tags[J]. 数据分析与知识发现, 2018, 2(7): 89-100.
[13] Xiufang Wang,Shu Sheng,Yan Lu. Analyzing Public Opinion from Microblog with Topic Clustering and Sentiment Intensity[J]. 数据分析与知识发现, 2018, 2(6): 37-47.
[14] Beibei Pang,Juanqiong Gou,Wenxin Mu. Extracting Topics and Their Relationship from College Student Mentoring[J]. 数据分析与知识发现, 2018, 2(6): 92-101.
[15] Wei Lu,Mengqi Luo,Heng Ding,Xin Li. Image Annotation Tags by Deep Learning and Real Users: A Comparative Study[J]. 数据分析与知识发现, 2018, 2(5): 1-10.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn