Ontology-based semantic search on the Web and its combination with the power of inductive reasoning

  • Claudia d’Amato
  • Nicola Fanizzi
  • Bettina Fazzinga
  • Georg Gottlob
  • Thomas Lukasiewicz


Semantic Web search is currently one of the hottest research topics in both Web search and the Semantic Web. In previous work, we have presented a novel approach to Semantic Web search, which allows for evaluating ontology-based complex queries that involve reasoning over the Web relative to an underlying background ontology. We have developed the formal model behind this approach, and provided a technique for processing Semantic Web search queries, which consists of an offline ontological inference step and an online reduction to standard Web search. In this paper, we continue this line of research. We further enhance the above approach by the use of inductive rather than deductive reasoning in the offline inference step. This increases the robustness of Semantic Web search, as it adds the important ability to handle inconsistencies, noise, and incompleteness, which are all very likely to occur in distributed and heterogeneous environments such as the Web. The inductive variant also allows to infer new (not logically deducible) knowledge (from training individuals). We report on a prototype implementation of (both the deductive and) the inductive variant of our approach in desktop search, and we provide extensive new experimental results, especially on the running time and the precision and the recall of our new approach.


Semantic search on the Web Ontologies Inductive reasoning Conjunctive queries Annotations Description logics Web search Semantic Web search Semantic Web Ontology reasoning Inconsistency Noise Incompleteness 

Mathematics Subject Classifications (2010)

68P15 68P20 68T27 68T30 68T35 68T37 68U35 


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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Claudia d’Amato
    • 1
  • Nicola Fanizzi
    • 1
  • Bettina Fazzinga
    • 2
  • Georg Gottlob
    • 3
  • Thomas Lukasiewicz
    • 4
  1. 1.Dipartimento di InformaticaUniversità degli Studi di BariBariItaly
  2. 2.Dipartimento di Elettronica, Informatica e SistemisticaUniversità della CalabriaRendeItaly
  3. 3.Department of Computer Science and Oxford-Man Institute of Quantitative FinanceUniversity of OxfordOxfordUK
  4. 4.Department of Computer ScienceUniversity of OxfordOxfordUK

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