Extending Faceted Search with Automated Object Ranking

  • Kostas Manioudakis
  • Yannis TzitzikasEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1057)


Faceted Search is a widely used interaction scheme in digital libraries, e-commerce, and recently also in Linked Data. Nevertheless, object ranking in the context of Faceted Search is not well studied. In this paper we propose an extended version of the model enriched with parameters that enable specifying the characteristics of the sought object ranking. Then we provide an algorithm for producing an object ranking that satisfies these parameters. For doing so various sources are exploited including preferences and statistical properties of the dataset. Finally we present an implementation of the model, the GUI extensions that were required, as well as simulation-based evaluation results that provide evidence about the reduction of the user’s cost.



This work was partially supported by the project AI4EU (EU H2020, Grant agreement No 825619).


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute of Computer ScienceFORTHHeraklionGreece
  2. 2.Computer Science DepartmentUniversity of CreteHeraklionGreece

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