语义网学习指南
时间：2009-07-23 来源：sinkingboat
1。本体是语义网的基础，如何理解本体，可以阅读以下论文：
N. Guarino and P. Giaretta, Ontologies and Knowledge Bases:Towards a Terminological Clarification. Toward Very Large Knowledge Bases: Knowledge Building and Knowledge Sharing. Amsterdam: IOS Press, 1995.
2.本体是如何用于语义网
基础的入门可以阅读以下论文：
T. Berners-Lee, J. Hendler, and O. Lassila, “The Semantic Web,”Scientific Am., http://www.sciam.com/2001/0501issue/0501berners-lee.html, 2001.
3.模糊逻辑用于处理不确定数据、关键字和本体
文本检索
M.Z. Islam and L. Brankovic, “A Framework for Privacy Preserving Data Mining,” Proc. Australasian Workshop Data Mining and Web Intelligence (DMWI ’04), pp. 163-168, 2004
搜索引擎
D.H. Widyantoro and J. Yen, “A Fuzzy Ontology-Based Abstract Search Engine and Its User Studies,” Proc. 10th IEEE Int’l Conf.Fuzzy Systems, pp. 1291-1294, 2001
4. FCA是一个数据分析和知识表示的有效技术。它定义了形式上下文去表示一个域中对象和属性之间的关系。从形式上下文中，FCA可以识别形式概念和集成相关概念格
FCA被用于不同的领域，比如文本处理、本体合并、email管理、e-learning、Web导航和专家系统。
B. Ganter and R. Wille, Formal Concept Analysis: Mathematical Foundations. Springer, 1999.
5.概念格
概念格现分为“传统概念格”、“模糊概念格”和“L-fuzzy格”
传统概念格的论文有：
模糊概念格的论文有：
2006,IEEE transaction,Automatic fuzzy ontology generation for semantic Web
L-fuzzy格的论文有：
5.聚类是最有效的本体识别技术之一。概念层的聚类技术比如COBWEB和CLASSIT是有效的聚类技术
D. Fisher, “Knowledge Acquisition via Incremental Conceptual Clustering,” Machine Learning, vol. 2, pp. 139-172, 1987.
J.H. Gennari, P. Langley, and D. Fisher, “Models of Incremental Concept Formation,” Machine Learning: Paradigms and Methods, pp. 11-62, 1990.
N. Guarino and P. Giaretta, Ontologies and Knowledge Bases:Towards a Terminological Clarification. Toward Very Large Knowledge Bases: Knowledge Building and Knowledge Sharing. Amsterdam: IOS Press, 1995.
2.本体是如何用于语义网
基础的入门可以阅读以下论文：
T. Berners-Lee, J. Hendler, and O. Lassila, “The Semantic Web,”Scientific Am., http://www.sciam.com/2001/0501issue/0501berners-lee.html, 2001.
3.模糊逻辑用于处理不确定数据、关键字和本体
文本检索
M.Z. Islam and L. Brankovic, “A Framework for Privacy Preserving Data Mining,” Proc. Australasian Workshop Data Mining and Web Intelligence (DMWI ’04), pp. 163-168, 2004
搜索引擎
D.H. Widyantoro and J. Yen, “A Fuzzy Ontology-Based Abstract Search Engine and Its User Studies,” Proc. 10th IEEE Int’l Conf.Fuzzy Systems, pp. 1291-1294, 2001
4. FCA是一个数据分析和知识表示的有效技术。它定义了形式上下文去表示一个域中对象和属性之间的关系。从形式上下文中，FCA可以识别形式概念和集成相关概念格
FCA被用于不同的领域，比如文本处理、本体合并、email管理、e-learning、Web导航和专家系统。
B. Ganter and R. Wille, Formal Concept Analysis: Mathematical Foundations. Springer, 1999.
5.概念格
概念格现分为“传统概念格”、“模糊概念格”和“L-fuzzy格”
传统概念格的论文有：
模糊概念格的论文有：
2006,IEEE transaction,Automatic fuzzy ontology generation for semantic Web
L-fuzzy格的论文有：
5.聚类是最有效的本体识别技术之一。概念层的聚类技术比如COBWEB和CLASSIT是有效的聚类技术
D. Fisher, “Knowledge Acquisition via Incremental Conceptual Clustering,” Machine Learning, vol. 2, pp. 139-172, 1987.
J.H. Gennari, P. Langley, and D. Fisher, “Models of Incremental Concept Formation,” Machine Learning: Paradigms and Methods, pp. 11-62, 1990.
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