An Architecture based in Voice Command Recognition for faceted search in Linked Open Datasets

  • Betia Lizbeth López-OchoaEmail author
  • José Luis Sánchez-Cervantes
  • Giner Alor-Hernández
  • Ma. Antonieta Abud-Figueroa
  • Beatriz A. Olivares-Zepahua
  • Lisbeth Rodríguez-Mazahua
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 688)


Faceted browsers have become a popular interface paradigm, since they combine the visualization of data that are part of a graph with data filtering techniques. On the other hand, NLP (Natural Language Processing) allows the use of everyday or natural language to interact with computer systems. LOD (Linked Open Data) cloud is the collection of datasets published in Linked Data format and covers a large number of domains, but the interaction with them is intended to be exploited by experts. Because of the problematic raised it is proposed the creation of an integration architecture for Linked Open datasets in a faceted browser with recognition of voice commands, so that through the NLP, on voice commands issued by the user, SPARQL queries will be generated to perform the search and navigation among the data stored in datasets available in the LOD cloud.


Faceted navigation Linked Data Natural Language Processing Voice recognition 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    A. Andrejs and J. McCrae, “The Linking Open Data cloud diagram,” 2017. [Online]. Available:
  2. 2.
    L. F. Sikos, Mastering Structured Data on the Semantic Web: From HTML5 Microdata to Linked Open Data. Apress, 2015.Google Scholar
  3. 3.
    J. Polowinski, “Widgets for faceted browsing,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5617 LNCS, no. PART 1, M. J. Smith and G. Salvendy, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009, pp. 601–610.Google Scholar
  4. 4.
    V. Tablan, K. Bontcheva, I. Roberts, and H. Cunningham, “Mímir: An open-source semantic search framework for interactive information seeking and discovery,” Web Semant. Sci. Serv. Agents World Wide Web, vol. 30, pp. 52–68, 2015.Google Scholar
  5. 5.
    A. Revuelta-Martínez, L. Rodríguez, I. García-Varea, and F. Montero, “Multimodal interaction for information retrieval using natural language,” Comput. Stand. Interfaces, vol. 35, no. 5, pp. 428–441, 2013.Google Scholar
  6. 6.
    D. Griol, J. M. Molina, and Z. Callejas, “A proposal for the development of adaptive spoken interfaces to access the Web,” Neurocomputing, vol. 163, pp. 56–68, 2015.Google Scholar
  7. 7.
    L. Heck et al., “Multimodal Conversational Search and Browse,” IEEE Work. Speech, Lang. Audio Multimed., pp. 96–101, 2013.Google Scholar
  8. 8.
    M. A. Paredes-Valverde, R. Valencia-García, M. Á. Rodríguez-García, R. Colomo-Palacios, and G. Alor-Hernández, “A semantic-based approach for querying linked data using natural language,” J. Inf. Sci., vol. 42, no. 6, pp. 851–862, 2016.Google Scholar
  9. 9.
    I. Habernal and M. Konopík, “SWSNL: Semantic Web Search Using Natural Language,” Expert Syst. Appl., vol. 40, no. 9, pp. 3649–3664, 2013.Google Scholar
  10. 10.
    M. A. Paredes-Valverde, M. Á. Rodríguez-García, A. Ruiz-Martínez, R. Valencia-García, and G. Alor-Hernández, “ONLI: An ontology-based system for querying DBpedia using natural language paradigm,” Expert Syst. Appl., vol. 42, no. 12, pp. 5163–5176, 2015.Google Scholar
  11. 11.
    F. J. Serón and C. Bobed, “VOX system: a semantic embodied conversational agent exploiting linked data,” Multimed. Tools Appl., vol. 75, no. 1, pp. 381–404, 2016.Google Scholar
  12. 12.
    A. Ben Abacha and P. Zweigenbaum, “MEANS: A medical question-answering system combining NLP techniques and semantic Web technologies,” Inf. Process. Manag., vol. 51, no. 5, pp. 570–594, 2015.Google Scholar
  13. 13.
    S. Auer, C. Bizer, G. Kobilarov, J. Lehmann, R. Cyganiak, and Z. Ives, “DBpedia: A Nucleus for a Web of Open Data,” in The Semantic Web: 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Korea, November 11-15, 2007. Proceedings, K. Aberer, K.-S. Choi, N. Noy, D. Allemang, K.-I. Lee, L. Nixon, J. Golbeck, P. Mika, D. Maynard, R. Mizoguchi, G. Schreiber, and P. Cudré-Mauroux, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007, pp. 722–735.Google Scholar
  14. 14.
    N. F. Noy et al., “BioPortal: ontologies and integrated data resources at the click of a mouse,” Nucleic Acids Res., vol. 37, no. suppl_2, pp. W170–W173, 2009.Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Betia Lizbeth López-Ochoa
    • 1
    Email author
  • José Luis Sánchez-Cervantes
    • 2
  • Giner Alor-Hernández
    • 1
  • Ma. Antonieta Abud-Figueroa
    • 1
  • Beatriz A. Olivares-Zepahua
    • 1
  • Lisbeth Rodríguez-Mazahua
    • 1
  1. 1.Division of Research and Postgraduate StudiesInstituto Tecnológico de OrizabaOrizabaMéxico
  2. 2.CONACYT- Instituto Tecnológico de OrizabaOrizabaMéxico

Personalised recommendations