Ontologies for conceptual modeling: their creation, use, and management
Data & Knowledge Engineering
Knowledge-Based Approaches to Query Expansion in Information Retrieval
AI '96 Proceedings of the 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
A fuzzy ontology for medical document retrieval
ACSW Frontiers '04 Proceedings of the second workshop on Australasian information security, Data Mining and Web Intelligence, and Software Internationalisation - Volume 32
Ontology-Based Information Retrieval Model for the Semantic Web
EEE '05 Proceedings of the 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'05) on e-Technology, e-Commerce and e-Service
An ontology-based information retrieval model
ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
A fuzzy ontology and its application to news summarization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
| Hi-index | 0.00 |
In this study, a semantic information retrieval system to access web content is proposed. Web pages existing in the web contain not only textual but also visual data. When textual and visual data are combined, the semantics of the information presented in a web page becomes richer. Consequently, types of text body and visual data are queried as one entity in a single query sentence to improve the precision, recall and rnorm parameters of a web query. Fuzzy domain ontology to fill the gap between raw content and semantic features is used, and a model namely OAC (Object, Action and Concept) is proposed. The core of our system is the OAC Model used for fuzzy domain ontology derivation. The OAC Model serves both images and texts, equally. Several experiments are carried out on selected real web pages, and good results are obtained.