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Ontology-Schema Based Query by Example
- Source :
- Conceptual Modeling ISBN: 9783030332228, ER
- Publication Year :
- 2019
- Publisher :
- Springer International Publishing, 2019.
-
Abstract
- The Web has evolved from a network of linked documents to one where both documents and data are linked, resulting in what is commonly known as the Web of Linked Data, that includes a large variety of data usually published in RDF from multiple domains. Intuitive ways of accessing RDF data become increasingly important since the standard approach would be to run SPARQL queries. However, this can be extremely difficult for non-experts users. In this paper, we address the problem of question answering over RDF. Given a natural language question or a keyword search string, our goal is to translate it into a formal query as SPARQL that captures the information needed. We propose Von-QBE which is a schema-based approach to query over RDF data without any previous knowledge about the ontology entities and schema. This is different from the-state-of-art since the approaches are instance-based. However, it can be unfeasible using such approaches in big data scenarios where the ontology base is huge and demands a large amount of computational resource to keep the knowledge base in memory. Moreover, most of these solutions need the knowledge base triplified, which can be a hard task for legacy bases. Von-QBE results are promising for the two real benchmarks evaluated, considering that only the ontology schema is used to generate SPARQL queries.
- Subjects :
- Information retrieval
business.industry
Computer science
Big data
InformationSystems_DATABASEMANAGEMENT
02 engineering and technology
computer.file_format
Linked data
Knowledge base
020204 information systems
ComputingMethodologies_DOCUMENTANDTEXTPROCESSING
0202 electrical engineering, electronic engineering, information engineering
Question answering
SPARQL
020201 artificial intelligence & image processing
Query by Example
RDF
business
computer
Natural language
computer.programming_language
Subjects
Details
- ISBN :
- 978-3-030-33222-8
- ISBNs :
- 9783030332228
- Database :
- OpenAIRE
- Journal :
- Conceptual Modeling ISBN: 9783030332228, ER
- Accession number :
- edsair.doi...........9cba0148187be1b6319a4eee518ac737