The Semantic Web began to emerge as its standards and technologies developed rapidly in the recent years. The continuing development of Semantic Web technologies has facilitated publishing explicit semantics with data on the Web in RDF data model. This study proposes a semantic search framework to support efficient keyword-based semantic search on RDF data utilizing near neighbor explorations. The framework augments the search results with the resources in close proximity by utilizing the entity type semantics. Along with the search results, the system generates a relevance confidence score measuring the inferred semantic relatedness of returned entities based on the degree of similarity. Furthermore, the evaluations assessing the effectiveness of the framework and the accuracy of the results are presented.
Dbpedia @cite_27 , FreeBase @cite_11 and many other large data sources provide a formal query end point for precise searching on the RDF data. There have been many approaches, e.g. @cite_31 adopting semantic searches based on user provided queries in a formal query language such as SPARQL. Use of formal query language-based systems have potential user adoption issues as they can be difficult to use even for technical users.
@cite_27 @cite_31 @cite_11
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DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web. DBpedia allows you to ask sophisticated queries against datasets derived from Wikipedia and to link other datasets on the Web to Wikipedia data. We describe the extraction of the DBpedia datasets, and how the resulting information is published on the Web for human-andmachine-consumption. We describe some emerging applications from the DBpedia community and show how website authors can facilitate DBpedia content within their sites. Finally, we present the current status of interlinking DBpedia with other open datasets on the Web and outline how DBpedia could serve as a nucleus for an emerging Web of open data. RDF and RDF Schema are two W3C standards aimed at enriching the Web with machine-processable semantic data.We have developed Sesame, an architecture for efficient storage and expressive querying of large quantities of metadata in RDF and RDF Schema. Sesame's design and implementation are independent from any specific storage device. Thus, Sesame can be deployed on top of a variety of storage devices, such as relational databases, triple stores, or object-oriented databases, without having to change the query engine or other functional modules. Sesame offers support for concurrency control, independent export of RDF and RDFS information and a query engine for RQL, a query language for RDF that offers native support for RDF Schema semantics. We present an overview of Sesame as a generic architecture, as well as its implementation and our first experiences with this implementation. Freebase is a practical, scalable tuple database used to structure general human knowledge. The data in Freebase is collaboratively created, structured, and maintained. Freebase currently contains more than 125,000,000 tuples, more than 4000 types, and more than 7000 properties. Public read write access to Freebase is allowed through an HTTP-based graph-query API using the Metaweb Query Language (MQL) as a data query and manipulation language. MQL provides an easy-to-use object-oriented interface to the tuple data in Freebase and is designed to facilitate the creation of collaborative, Web-based data-oriented applications.