The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
A Review of Fuzzy Models for the Semantic Web
|
|
Author(s): Hailong Wang (Northeastern University, China), Zongmin Ma (Northeastern University, China), Li Yan (Northeastern University, China)and Jingwei Cheng (Northeastern University, China)
Copyright: 2010
Pages: 15
Source title:
Web Technologies: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Arthur Tatnall (Victoria University, Australia)
DOI: 10.4018/978-1-60566-982-3.ch005
Purchase
|
Abstract
In the Semantic Web context, information would be retrieved, processed, shared, reused and aligned in the maximum automatic way possible. Our experience with such applications in the Semantic Web has shown that these are rarely a matter of true or false but rather procedures that require degrees of relatedness, similarity, or ranking. Apart from the wealth of applications that are inherently imprecise, information itself is many times imprecise or vague. In order to be able to represent and reason with such type of information in the Semantic Web, different general approaches for extending semantic web languages with the ability to represent imprecision and uncertainty has been explored. In this chapter, we focus our attention on fuzzy extension approaches which are based on fuzzy set theory. We review the existing proposals for extending the theoretical counterpart of the semantic web languages, description logics (DLs), and the languages themselves. The following statements will include the expressive power of the fuzzy DLs formalism and its syntax and semantic, knowledge base, the decidability of the tableaux algorithm and its computational complexity etc. Also the fuzzy extension to OWL is discussed in this chapter.
Related Content
|
Dina Darwish.
© 2024.
28 pages.
|
|
Dina Darwish.
© 2024.
28 pages.
|
|
Muhammad Ahmed, Adnan Ahmad, Furkh Zeshan, Hamid Turab.
© 2024.
33 pages.
|
|
Pankaj Bhambri.
© 2024.
17 pages.
|
|
Kaushikkumar Patel.
© 2024.
20 pages.
|
|
Vijaya Kittu Manda, Arnold Mashud Abukari, Vivek Gupta, Madavarapu Jhansi Bharathi.
© 2024.
24 pages.
|
|
Pankaj Bhambri.
© 2024.
17 pages.
|
|
|