Authors:
Angelo Batista Neves
1
;
Luiz André P. Paes Leme
2
;
Yenier Torres Izquierdo
1
and
Marco Antonio Casanova
1
Affiliations:
1
Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
;
2
Universidade Federal Fluminense, Niterói, RJ, Brazil
Keyword(s):
Benchmark, Keyword Search, Resource Description Framework (RDF), Offline, Computation.
Abstract:
Keyword search systems provide users with a friendly alternative to access Resource Description Framework (RDF) datasets. The evaluation of such systems requires adequate benchmarks, consisting of RDF datasets and keyword queries, with their correct answers. However, the sets of correct answers such benchmarks provide for each query are often incomplete, mostly because they are manually built with experts’ help. The central contribution of this paper is an offline method that helps build RDF keyword search benchmarks automatically, leading to more complete sets of correct answers, called solution generators. The paper focuses on computing sets of generators and describes heuristics that circumvent the combinatorial nature of the problem. The paper then describes five benchmarks, constructed with the proposed method and based on three real datasets, DBpedia, IMDb, and Mondial, and two synthetic datasets, LUBM and BSBM. Finally, the paper compares the constructed benchmarks with keywor
d search benchmarks published in the literature.
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