On Faceted Search over Knowledge Bases.
Bernardo Cuenca Grau, Evgeny Kharlamov, Dmitriy Zheleznyakov, Marcelo Arenas, Šarūnas Marciuška · 2014
[3] for storing, publishing, and querying semistructured data. The functionality of many such applications is enhanced with OWL 2 ontologies [1], which are used to provide a conceptual layer on top of data and enrich query answers with implicit information. Although the growing popularity of RDF, OWL 2, and SPARQL 1.1 has been ac-companied by the development of better and better query answering engines, writing SPARQL 1.1 queries is not well-suited for the majority of users. Thus, an important challenge is the development of simple yet powerful query interfaces that capture well-defined fragments of SPARQL 1.1. Faceted search is a prominent approach for accessing document collections that allows users to narrow down search results by incrementally applying filters, called facets, on the annotations associated to documents [18]. Faceted search has become a mainstream commercial technology, and it is ubiquitous in e-commerce websites. For example, hotel booking websites such as Booking.com allow users to refine search results by selecting suitable values in facets such as ‘Price’, ‘Star Rating’, or ‘Facilities’. Faceted search has been proposed as a suitable paradigm for querying document