SemIndex: Semantic-Aware Inverted Index

  • Richard Chbeir
  • Yi Luo
  • Joe Tekli
  • Kokou Yetongnon
  • Carlos Raymundo Ibañez
  • Agma J. M. Traina
  • Caetano TrainaJr.
  • Marc Al Assad
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8716)


This paper focuses on the important problem of semantic-aware search in textual (structured, semi-structured, NoSQL) databases. This problem has emerged as a required extension of the standard containment keyword based query to meet user needs in textual databases and IR applications. We provide here a new approach, called SemIndex, that extends the standard inverted index by constructing a tight coupling inverted index graph that combines two main resources: a general purpose semantic network, and a standard inverted index on a collection of textual data. We also provide an extended query model and related processing algorithms with the help of SemIndex. To investigate its effectiveness, we set up experiments to test the performance of SemIndex. Preliminary results have demonstrated the effectiveness, scalability and optimality of our approach.


Semantic Queries Inverted lndex NoSQL indexing Semantic Network Ontologies 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Richard Chbeir
    • 1
  • Yi Luo
    • 2
  • Joe Tekli
    • 3
  • Kokou Yetongnon
    • 2
  • Carlos Raymundo Ibañez
    • 4
  • Agma J. M. Traina
    • 5
  • Caetano TrainaJr.
    • 5
  • Marc Al Assad
    • 3
  1. 1.University of Pau and Adour CountriesAngletFrance
  2. 2.University of BourgogneDijonFrance
  3. 3.Lebanese American UniversityByblosLebanon
  4. 4.Universidad Peruana de Ciencias AplicadasLimaPeru
  5. 5.University of São PauloSão Carlos-SPBrazil

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