The lack of familiarity that most users have with information systems has led to a variety of methods to access data in a flexible way (such as keyword search, faceted search, and similarity search). However, capabilities of flexible query answering are hard to integrate in one system since they are based on different data representations and relies on different techniques for query answering. The problem becomes more involved if we need to query heterogeneous data sources. To address such variety in one fell swoop, we propose FleQSy, a framework that relies on a “meta” approach for accessing heterogeneous data with different methods for flexible query answering. In FleQSy structured and semi-structured data sources are modeled as graphs and query answering consists of a multi-phase process that leverages the commonalities of the various search techniques. We show the effectiveness of our approach in different application scenarios that require easy-to-use and elastic methods for data access.
DE VIRGILIO, R., Maccioni, A., Torlone, R. (2016). A unified framework for flexible query answering over heterogeneous data sources. In Advances in Intelligent Systems and Computing (pp.283-294). Springer Verlag [10.1007/978-3-319-26154-6_22].