[1] Yan Duanwu, Li Xiaopeng, Wang Lei, Cheng Xiao, et al. Ontology-based similarity measure for text clustering [J]. Journal of Southeast University (English Edition), 2006, 22 (3): 389-393. [doi:10.3969/j.issn.1003-7985.2006.03.021]
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Ontology-based similarity measure for text clustering(
)
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 22
- Issue:
- 2006 3
- Page:
- 389-393
- Research Field:
- Computer Science and Engineering
- Publishing date:
- 2006-09-30
Info
- Title:
- Ontology-based similarity measure for text clustering
- Author(s):
- Yan Duanwu1; Li Xiaopeng2; Wang Lei1; Cheng Xiao1
-
1Department of Information Management, Nanjing University of Science and Technology, Nanjing 210094, China
2Library, Nanjing University of Science and Technology, Nanjing 210094, China
- PACS:
- TP391.1
- DOI:
- 10.3969/j.issn.1003-7985.2006.03.021
- Abstract:
- A method that combines category-based and keyword-based concepts for a better information retrieval system is introduced.To improve document clustering, a document similarity measure based on cosine vector and keywords frequency in documents is proposed, but also with an input ontology.The ontology is domain specific and includes a list of keywords organized by degree of importance to the categories of the ontology, and by means of semantic knowledge, the ontology can improve the effects of document similarity measure and feedback of information retrieval systems.Two approaches to evaluating the performance of this similarity measure and the comparison with standard cosine vector similarity measure are also described.
References:
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Memo
- Memo:
- Biography: Yan Duanwu(1976—), male, doctor, lecturer, yanwu-nju@163.com.