Towards a framework for graph-based keyword search over relational data. (17th February 2022)

• Record Type: Journal Article
• Authors: Cozza, Vittoria
• Is Part Of: International journal of intelligent information and database systems. Volume 15:Number 2(2022)
• Page Start: 183
• Page End: 198
• Publication Date: 2022-02-17
• Subjects: relational data -- database search -- structured data -- graph search -- keyword search -- database applications -- knowledge management applications; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

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.