Today, the need to deal with ambiguous information in semantic web languages is increasing. Ontology is an important part of the W3C standards for the semantic web, used to define a conceptual standard vocabulary for the exchange of data between systems, the provision of reusable databases, and the facilitation of collaboration across multiple systems. However, classical ontology is not enough ...

First, Similarity Of Fuzzy Ontology Generation For Semantic Web, Fuzzy Formal Concept Analysis incorporates fuzzy logic into Formal Concept Analysis (FCA) to form a fuzzy concept lattice. The fuzzy ontology is an extension of the domain ontology for solving the uncertainty problems. Fuzzy Conceptual Clustering then constructs the concept hierarchy from the fuzzy concept lattice. Finally, Fuzzy ...

Ontology is an important part of the W3C standards for the Semantic Web used to specify standard conceptual vocabularies to exchange data among systems, provide reusable knowledge bases, and facilitate interoperability across multiple heterogeneous systems and databases. However, current ontology is not sufficient for handling vague information that is commonly found in many application domains...

Due to the increasing web, there are many challenges to establish a general framework for data mining and retrieving structured data from the Web. Creating an ontology is a step towards solving this problem. The ontology raises the main entity and the concept of any data in data mining. In this paper, we tried to propose a method for applying the "meaning" of the search system, But the problem ...

This paper proposes the FOGA (Fuzzy Ontology Generation frAmework) for automatic generation of fuzzy ontology on uncertainty information. The FOGA framework comprises the following components: Fuzzy Formal Concept Analysis, Fuzzy Conceptual Clustering and Fuzzy Ontology Generation. First, Fuzzy Formal Concept Analysis incorporates fuzzy logic into Formal Concept Analysis (FCA) to form a fuzzy c...

Ontology is the basis of sharing and reusing knowledge on the Semantic Web, and ontology-based semantic retrieval is a hotspot of current research. Fuzzy ontology is an extension of domain ontology for solving the uncertainty problems. To represent fuzzy knowledge more effectively, this paper presents a new series of fuzzy ontology models that consists of fuzzy domain ontology and fuzzy linguis...

Ontology is an effective conceptualism commonly used for the World Wide Web. Fuzzy logic can be incorporated to ontology to represent uncertainty information. To tackle this problem, this paper proposes the FOGA (Fuzzy Ontology Generation framework) for automatic generation of fuzzy ontology on uncertainty information. The FOGA framework comprises the following components: Fuzzy Formal Concept ...

Ontology is the basis of sharing and reusing knowledge on the semantic web. The fuzzy ontology is an extension of the domain ontology for solving the uncertainty problems. Although many earlier methods tried to create a fuzzy ontology and applied it to documents summarization, none of the previous methods have discussed Arabic document summarization using FA fuzzy ontology which could benefit f...

We present a novel approach to representing uncertain information in ontologies based on design patterns. We provide a brief description of our approach, present its use in case of fuzzy information and probabilistic information, and describe the possibility to model multiple types of uncertainty in a single ontology. We also shortly present an appropriate fuzzy reasoning tool and define a comp...

This paper proposes an ontology which enables fuzzy data to be defined in order to conceptualize them and to represent another type of information. The Fuzzy Knowledge Representation Ontology described is based on the fuzzy data theoretical model, and a method for classifying both classical and fuzzy data is proposed. This ontology defines a framework for storing fuzzy information in fuzzy data...