Towards Verbalizing SPARQL Queries in Arabic
نویسندگان
چکیده
منابع مشابه
SPARTIQULATION: Verbalizing SPARQL Queries
Much research has been done to combine the fields of Databases and Natural Language Processing. While many works focus on the problem of deriving a structured query for a given natural language question, the problem of query verbalization – translating a structured query into natural language – is less explored. In this work we describe our approach to verbalizing SPARQL queries in order to cre...
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The most common way for exposing RDF data on the Web is by means of SPARQL endpoints. These endpoints are Web services that implement the SPARQL protocol and then allow end users and applications to query just the RDF data they want. However the servers hosting the SPARQL endpoints restrict the access to the data by limiting the amount of results returned by user queries or the amount of querie...
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SPARQL has become the most popular language for querying RDF datasets, the standard data model for representing information in the Web. This query language has received a good deal of attention in the last few years: two versions of W3C standards have been issued, several SPARQL query engines have been deployed, and important theoretical foundations have been laid. However, many fundamental asp...
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Querying over cached indexes of Linked Data often suffers from stale or missing results due to infrequent updates and partial coverage of sources. Conversely, live decentralised approaches offer fresh results directly from the Web, but exhibit slow response times due to accessing numerous remote sources at runtime. We thus propose a hybrid query approach that improves upon both paradigms, offer...
متن کاملProvenance for SPARQL Queries
Determining trust of data available in the Semantic Web is fundamental for applications and users, in particular for linked open data obtained from SPARQL endpoints. There exist several proposals in the literature to annotate SPARQL query results with values from abstract models, adapting the seminal works on provenance for annotated relational databases. We provide an approach capable of provi...
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ژورنال
عنوان ژورنال: Engineering, Technology & Applied Science Research
سال: 2016
ISSN: 1792-8036,2241-4487
DOI: 10.48084/etasr.630