RDF datasets are becoming increasingly useful with the development of knowledge-based web applications. SPARQL is the official structured query language to search and access RDF datasets. Despite its effectiveness, the language is often difficult to use for non-experts because of its syntax and the necessity to know the underlying data structure of the database queries. In this regard, keyword search enables non-expert users to access the data contained in RDF datasets intuitively. This work describes the TSA+VDP keyword search system for effective and efficient keyword search over large RDF datasets. The system is compared with other state-of-the-art methods on different datasets, both real-world and synthetic, using a new evaluation framework that is easily reproducible and sharable.

A Scalable Virtual Document-Based Keyword Search System for RDF Datasets

DOSSO, DENNIS
;
Gianmaria Silvello
2019

Abstract

RDF datasets are becoming increasingly useful with the development of knowledge-based web applications. SPARQL is the official structured query language to search and access RDF datasets. Despite its effectiveness, the language is often difficult to use for non-experts because of its syntax and the necessity to know the underlying data structure of the database queries. In this regard, keyword search enables non-expert users to access the data contained in RDF datasets intuitively. This work describes the TSA+VDP keyword search system for effective and efficient keyword search over large RDF datasets. The system is compared with other state-of-the-art methods on different datasets, both real-world and synthetic, using a new evaluation framework that is easily reproducible and sharable.
2019
Proc. of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval
42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019
9781450361729
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3301034
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