RDF-F: RDF Datatype inFerring Framework

Abstract

In the context of RDF document matching/integration, the datatype information, which is related to literal objects, is an important aspect to be analyzed in order to better determine similar RDF documents. In this paper, we present an RDF Datatype in Ferring Framework, called RDF-F, which provides two independent datatype inference processes: 1) a fourstep process consisting of (i) a predicate information analysis (i.e., deduce the datatype from existing range property), (ii) an analysis of the object value itself by a pattern-matching process (i.e., recognize the object lexical space), (iii) a semantic analysis of the predicate name and its context, and (iv) generalization of Numeric and Binary datatypes to ensure the integration; and 2) a non-ambiguous lexical-space-matching process, where literal values are inferred by the modification of their representation, following new lexical spaces. We evaluated the performance and the accuracy of both processes with datasets from DBpedia. Results show that the execution time of both indicators is linear and their accuracy can increase up to 97.10 and 99.30%, respectively.

Towards Automatic Mathematical Exercise Solving

“…Since knowledge graphs can provide well-structured information and relations of the entities, it is known to be useful to do reasoning in many tasks, such as query answering and relation inference (i.e. to infer missing relations in the knowledge graph [10,21,22]). Gu et al [15] proposed a technique to answer queries on knowledge graph by "compositionalizing" a broad class of vector space models, which performs well on query answering and knowledge graph completion.…”

RiAiR: A Framework for Sensitive RDFProtection

“…The algorithm for external nodes receives a set of triples T = replaceListNodes.add(Pair(t i .s,t j .s)); 10 break; //Since a similar node was found, the next t i is analyzed. 11 T' = T.replaceNodes(replaceListNodes); // Nodes are replaced. 12 T' = T'.removeDuplicateTriples(); //Duplicate triples are removed.…”

“…10 break; //Since a similar node was found, the next t i is analyzed. 11 T' = T.removeTriples(removeListTriples); //Triples of removeListTriples list are removed. 12 return T';…”

“…For the intersection phase, new semantic similarity functions are required to recognize potential keys that are not from the same domain (e.g., SameAs service). Additionally, the datasets can be enriched with new properties (relations) or extra inferred information as a pre-step in order to better perform the similarities (e.g., syntactic and semantic datatype inference as in [11,18], respectively). model and anonymization technique; and machine/deep learning techniques for an analysis and classification of data to discover patters and gesture recognition.…”

Princípios para avaliação de vocabulários controlados

“…O RDF é utilizado para descrever recursos que representam a abstração de uma entidade (documento, conceito abstrato, pessoa, empresa, etc.). O modelo de dados RDF usa o Internationalized Resource Identifier (IRI), nós em branco e nós literais como elementos para criar triplas e fornecer relacionamentos entre recursos(Dongo;Cardinale;Chbeir, 2018).Turtle e and TriG, JSON-LD, RDFa, N-Triples e N-Quads e RDF/XML. O RDF possui uma sintaxe própria também chamada de vocabulário RDF, que basicamente diz respeito ao uso de elementos descritivos que expressam atributos pré-definidos.…”