On The Marriage of SPARQL and Keywords
Peng Peng, Lei Zou, Dongyan Zhao

TL;DR
This paper introduces a hybrid query paradigm combining SPARQL and keyword search to improve query expressiveness and precision over RDF graphs, supported by a novel index and algorithm.
Contribution
The paper proposes a new SK query model that integrates SPARQL and keywords, along with a structural index and query algorithm for efficient processing.
Findings
Effective in large RDF graphs
Demonstrates improved query accuracy
Shows high efficiency in experiments
Abstract
Although SPARQL has been the predominant query language over RDF graphs, some query intentions cannot be well captured by only using SPARQL syntax. On the other hand, the keyword search enjoys widespread usage because of its intuitive way of specifying information needs but suffers from the problem of low precision. To maximize the advantages of both SPARQL and keyword search, we introduce a novel paradigm that combines both of them and propose a hybrid query (called an SK query) that integrates SPARQL and keyword search. In order to answer SK queries efficiently, a structural index is devised, based on a novel integrated query algorithm is proposed. We evaluate our method in large real RDF graphs and experiments demonstrate both effectiveness and efficiency of our method.
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Taxonomy
TopicsSemantic Web and Ontologies · Graph Theory and Algorithms · Advanced Graph Neural Networks
