Keyword-based access to structured data has attracted research and industry as a means for facilitating access to information. In recent years, the research community and big data technology vendors put a lot of effort into developing new proof of concept systems for the task at hand. Two major limitations have been identified for such prototypes to transition into fully developed products: 1) systems are not designed to scale up; 2) the absence of a complete evaluation approach oriented towards effectiveness. This work presents a framework for supporting the development and the evaluation of graph-based keyword search systems. Furthermore, the implementation of a core module of this framework is detailed and shared open-source with the community.

Towards a framework for graph-based keyword search over relational data

Cozza, Vittoria
2022-01-01

Abstract

Keyword-based access to structured data has attracted research and industry as a means for facilitating access to information. In recent years, the research community and big data technology vendors put a lot of effort into developing new proof of concept systems for the task at hand. Two major limitations have been identified for such prototypes to transition into fully developed products: 1) systems are not designed to scale up; 2) the absence of a complete evaluation approach oriented towards effectiveness. This work presents a framework for supporting the development and the evaluation of graph-based keyword search systems. Furthermore, the implementation of a core module of this framework is detailed and shared open-source with the community.
2022
database applications; database search; graph search; keyword search; knowledge management applications; relational data; structured data
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12079/72767
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