Abstract
Structured data sources promise to be the next driver of a significant socio-economic impact for both people and companies. Nevertheless, accessing them through formal languages, such as SQL or SPARQL, can become cumbersome and frustrating for end-users. To overcome this issue, keyword search in databases is becoming the technology of choice, even if it suffers from efficiency and effectiveness problems that prevent it from being adopted at Web scale.
In this paper, we motivate the need for a reference architecture for keyword search in databases to favor the development of scalable and effective components, also borrowing methods from neighbor fields, such as information retrieval and natural language processing. Moreover, we point out the need for a companion evaluation framework, able to assess the efficiency and the effectiveness of such new systems and in the light of real and compelling use cases.
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Bergamaschi, S., Ferro, N., Guerra, F., Silvello, G. (2016). Keyword-Based Search Over Databases: A Roadmap for a Reference Architecture Paired with an Evaluation Framework. In: Nguyen, N.T., Kowalczyk, R., Rupino da Cunha, P. (eds) Transactions on Computational Collective Intelligence XXI. Lecture Notes in Computer Science(), vol 9630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49521-6_1
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