[1] Liu Baisong, Gao Ji,. General ontology learning framework [J]. Journal of Southeast University (English Edition), 2006, 22 (3): 381-384. [doi:10.3969/j.issn.1003-7985.2006.03.019]
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General ontology learning framework(
)
通用本体学习框架研究
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 22
- Issue:
- 2006 3
- Page:
- 381-384
- Research Field:
- Computer Science and Engineering
- Publishing date:
- 2006-09-30
Info
- Title:
- General ontology learning framework
- 通用本体学习框架研究
- Author(s):
- Liu Baisong1; 2; Gao Ji1
-
1College of Computer Science, Zhejiang University, Hangzhou 310027, China
2Network Center, Ningbo University, Ningbo 315211, China
- Keywords:
- ontology; ontology learning; ontology evaluation; semantic web
- PACS:
- TP312.1
- DOI:
- 10.3969/j.issn.1003-7985.2006.03.019
- Abstract:
- In order to reduce the costs of the ontology construction, a general ontology learning framework(GOLF)is developed.The key technologies of the GOLF including domain concepts extraction and semantic relationships between concepts and taxonomy automatic construction are proposed.At the same time ontology evaluation methods are also discussed.The experimental results show that this method produces better performance and it is applicable across different domains.By integrating several machine learning algorithms, this method suffers less ambiguity and can identify domain concepts and relations more accurately.By using generalized corpus WordNet and HowNet, this method is applicable across different domains.In addition, by obtaining source documents from the web on demand, the GOLF can produce up-to-date ontologies.
- 提出了一种通用本体学习框架GOLF, 通过对网络上各专业领域web文档集进行挖掘来实现本体自动构建, 讨论了本体学习中本体概念的抽取、概念之间语义关系的抽取和分类体系的自动构建等关键技术, 通过实验对算法进行了测试, 并对本体评价方法进行了探讨.由于集成了多种机器学习算法, 该方法在概念抽取和语义关系学习方面具有更高的准确性.采用通用本体WordNet和HowNet作为语料库, 它可适用于不同的专业领域.同时, 通过按需获取web文档, 该方法能实时生成本体.
References:
[1] Buitelaar P, Handschuh S, Magnini B.ECAI workshop on ontology learning and population:towards evaluation of text-based methods in the semantic web and knowledge discovery life cycle[A].In:The 16th European Conference on Artificial Intelligence[C].Valencia, Spain, 2004.1-6.
[2] Navigli R, Velardi P.Ontology enrichment through automatic semantic annotation of on-line glossaries [A].In:Proc of the 15th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2006), LNAI[C].Podebrady, Czech Republic, Springer, 2006, 4248:126-140.
[3] Brank Janez, Mladenic Dunja, Grobelnik Marko.Golden standard based ontology evaluation using instance assignment [A].In:The 4th International EON Workshop[C].Edinburgh, United Kingdom, 2006.47-54.
[4] Buitelaar P, Olejnik D, Sintek M.OntoLT:a protégé plug-in for ontology extraction from text [A].In:Proceedings of the International Semantic Web Conference (ISWC)[C].Florida, USA, 2003.17-22.
[5] Velardi P, Navigli R, Cuchiarelli A, et al.Evaluation of ontoLearn, a methodology for automatic learning of domain ontologies[A].In:Ontology Learning from Text:Methods, Evaluation and Applications [C].IOS Press, 2005.1-32.
[6] Sabou Marta.Learning web service ontologies:an automatic extraction method and its evaluation [A].In:ISWC2005[C].Osaka, Japan, 2005.98-116.
[7] Cimiano P, Staab S, Tane J.Automatic acquisition of taxonomies from text: FCA meets NLP[A].In:ECML/PKDD Workshop on Adaptive Text Extraction and Mining[C].Cavtat-Dubrovnik, Croatia, 2003.10-17.
[8] Thanh Tho Quan, Siu Cheung Hui, ACM Fong, et al.Automatic generation of ontology for scholarly semantic web[A].In:ISWC2004, LNCS[C].Hiroshima, Japan, 2004, 3298:726-740.
[9] Maedche A, Staab S.Measuring similarity between ontologies [A].In:Proceedings of European Knowledge Acquisition Workshop (EKAW2002)[C].Madrid, Spain, 2002.251-263.
[10] Maedche A, Staab S.Ontology learning for the semantic web [J].IEEE Intelligent Systems, 2001, 16(2):72-79.
Memo
- Memo:
- Biographies: Liu Baisong(1971—), male, graduate, associate professor, lbs@nbu.edu.cn;Gao Ji(corresponding author), male, professor, gaoji@mail.hz.zj.cn.