Information retrieval by constrained spreading activation in semantic networks
Information Processing and Management: an International Journal - Artificial Intelligence and Information Retrieval
A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Application of Spreading Activation Techniques in InformationRetrieval
Artificial Intelligence Review
The nature of mathematical modeling
The nature of mathematical modeling
Communications of the ACM
Encyclopedia of Artificial Intelligence
Encyclopedia of Artificial Intelligence
Neural Networks for Statistical Modeling
Neural Networks for Statistical Modeling
WWW '03 Proceedings of the 12th international conference on World Wide Web
A spreading activation network model for information retrieval
A spreading activation network model for information retrieval
SemRank: ranking complex relationship search results on the semantic web
WWW '05 Proceedings of the 14th international conference on World Wide Web
RSS: A framework enabling ranked search on the semantic web
Information Processing and Management: an International Journal
A survey and classification of semantic search approaches
International Journal of Metadata, Semantics and Ontologies
Web Semantics: Science, Services and Agents on the World Wide Web
Ranking semantic relationships between two entities using personalization in context specification
Information Sciences: an International Journal
Hi-index | 12.05 |
As the information on the Internet dramatically increases, more and more limitations in information searching are revealed, because web pages are designed for human use by mixing content with presentation. In order to overcome these limitations, the Semantic Web, based on ontology, was introduced by W3C to bring about significant advancement in web searching. To accomplish this, the Semantic Web must provide search methods based on the different relationships between resources. In this paper, we propose a semantic association search methodology that consists of the evaluation of resources and relationships between resources, as well as the identification of relevant information based on ontology, a semantic network of resources and properties. The proposed semantic search method is based on an extended spreading activation technique. In order to evaluate the importance of a query result, we propose weighting methods for measuring properties and resources based on their specificity and generality. From this work, users can search semantically associated resources for their query, confident that the information is valuable and important. The experimental results show that our method is valid and efficient for searching and ranking semantic search results.