Practical RDF Schema Reasoning with Annotated Semantic Web Data

Damásio, Carlos Viegas; Ferreira, Filipe

doi:10.1007/978-3-642-25073-6_47

Cited by 2 publications

(1 citation statement)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, the works in [11] demonstrated a context-aware approach to keyword query interpretation, which addresses the novel problem of using a sequence of structured queries corresponding to interpretations of keyword queries. Similarly, a considerable number of studies have been attempted into proposed approaches to RDF query [15][16][17][18].…”

Section: Related Workmentioning

confidence: 99%

A Novel Approach for Accessing Semantic Data by Translating RESTful/JSON Commands into SPARQL Messages

Nguyen¹,

Nguyễn²,

Huynh³

2016

IEIE Transactions on Smart Processing and Computing

View full text Add to dashboard Cite

Linked Data is a powerful technology for storing and publishing the structures of data. It is helpful for web applications because of its usefulness through semantic query data. However, using Linked Data is not easy for ordinary users who lack knowledge about the structure of data or the query syntax of Linked Data. For that problem, we propose a translator component that is used for translating RESTful/JSON request messages into SPARQL commands based on ontology -a metadata that describes the structure of data. Clients do not need to worry about the structure of stored data or SPARQL, a kind of query language used for querying linked data that not many people know, when they insert a new instance or query for all instances of any specific class with those complex structure data. In addition, the translator component has the search function that can find a set of data from multiple classes based on finding the shortest paths between the target classes -the original set that user provide, and target classes-the users want to get. This translator component will be applied for any dynamic ontological structure as well as automatically generate a SPARQL command based on users' request message.

show abstract

Section: Related Workmentioning

confidence: 99%

A Novel Approach for Accessing Semantic Data by Translating RESTful/JSON Commands into SPARQL Messages

Nguyen¹,

Nguyễn²,

Huynh³

2016

IEIE Transactions on Smart Processing and Computing

View full text Add to dashboard Cite

show abstract

RDFS Reasoning on Massively Parallel Hardware

Heino

Pan

2012

The Semantic Web – ISWC 2012

View full text Add to dashboard Cite

Recent developments in hardware have shown an increase in parallelism as opposed to clock rates. In order to fully exploit these new avenues of performance improvement, computationally expensive workloads have to be expressed in a way that allows for fine-grained parallelism. In this paper, we address the problem of describing RDFS entailment in such a way. Different from previous work on parallel RDFS reasoning, we assume a shared memory architecture. We analyze the problem of duplicates that naturally occur in RDFS reasoning and develop strategies towards its mitigation, exploiting all levels of our architecture. We implement and evaluate our approach on two real-world datasets and study its performance characteristics on different levels of parallelization. We conclude that RDFS entailment lends itself well to parallelization but can benefit even more from careful optimizations that take into account intricacies of modern parallel hardware.

show abstract

Practical RDF Schema Reasoning with Annotated Semantic Web Data

Cited by 2 publications

References 26 publications

A Novel Approach for Accessing Semantic Data by Translating RESTful/JSON Commands into SPARQL Messages

A Novel Approach for Accessing Semantic Data by Translating RESTful/JSON Commands into SPARQL Messages

RDFS Reasoning on Massively Parallel Hardware

Contact Info

Product

Resources

About