An RDF Storage and Query Framework with Flexible Inference Strategy

Autor:	Yuzhong Qu, Wennan Shen
Rok vydání:	2006
Předmět:	Computer science Backward chaining RDF Schema Inference computer.file_format computer.software_genre RDF/XML Metadata Data set Forward chaining SPARQL Data mining RDF Inference engine Cwm Semantic Web computer RDF query language computer.programming_language
Zdroj:	Frontiers of WWW Research and Development-APWeb 2006 ISBN: 9783540311423 APWeb
DOI:	10.1007/11610113_16
Popis:	In the Semantic Web, RDF (Resource Description Framework) and RDF Schema are commonly used to describe metadata. There are a great many RDF data in current web, therefore, efficient storage and retrieval of large RDF data sets is required. So far, several RDF storage and query system are developed. According to the inference strategy they used, they can be classified into two categories, one exclusively use forward chaining strategy; the other exclusively use backward chaining strategy. In most cases, the query performance of the former is superior to that of the latter. However, in some cases, the disadvantage of larger storage space may at some point outweigh the advantage of faster querying. Further, the existing systems that exclusively use forward chaining strategy have not yet presented a good solution to the deletion operation by now. In this paper, we design a RDF storage and query framework with flexible inference strategy, which can combine forward and backward chaining inference strategies. In addition, a new solution to the deletion operation is also given within our framework. The feasibility of our framework is illustrated by primary experiments.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::b6bb2153666598cd4737442d5c75e7ec https://doi.org/10.1007/11610113_16 Zobrazit plný text záznamu