Inferring the semantic properties of sentences by mining syntactic parse trees
Data & Knowledge Engineering
Journal of Biomedical Informatics
Machine learning of syntactic parse trees for search and classification of text
Engineering Applications of Artificial Intelligence
A review of ranking approaches for semantic search on Web
Information Processing and Management: an International Journal
A recommendation framework for remote sensing images by spatial relation analysis
Journal of Systems and Software
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With the tremendous growth of information available to end users through the Web, search engines come to play ever a more critical role. Nevertheless, because of their general purpose approach, it is always less uncommon that obtained result sets provide a burden of useless pages. Next generation Web architecture, represented by Semantic Web, provides the layered architecture possibly allowing to overcome this limitation. Several search engines have been proposed, which allow to increase information retrieval accuracy by exploiting a key content of Semantic Web resources, that is relations. However, in order to rank results, most of the existing solutions need to work on the whole annotated knowledge base. In this paper we propose a relation-based page rank algorithm to be used in conjunction with Semantic Web search engines that simply relies on information which could be extracted from user query and annotated resource. Relevance is measured as the probability that retrieved resource actually contains those relations whose existence was assumed by the user at the time of query definition.