Skip to main content
SpringerLink
Log in
SpringerLink
Log in

Requirements to Modern Semantic Search Engine

  • Conference paper
  • First Online:
Knowledge Engineering and Semantic Web (KESW 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 649))

Included in the following conference series:

Abstract

Since the introduction of computing machines into companies and industries, searching large enterprise data is an open challenge including diverse and distributed datasets, missing alignment of vocabularies within divisions as well as data isolated in format silos. In this article, we report the requirements of commercial enterprises to the next generation of semantic search engine for large, distributed data. We describe our elicitation process to gather end user requirements, the challenges arising for real-world use cases as well as how such an implementation of this paradigm can be benchmarked. In the end, we present the design of the DIESEL search engine, which aims to implement the requirements of commercial enterprise to semantic search.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    http://www.diesel-project.eu.

  2. 2.

    https://www.wikidata.org/wiki/Special:Statistics.

  3. 3.

    https://query.wikidata.org/.

  4. 4.

    http://qald.sebastianwalter.org/.

  5. 5.

    http://www.okbqa.org/.

  6. 6.

    http://metaphacts.com/wikidata.

  7. 7.

    At the 22nd April, we gathered 13 responses. In the online version you can also see preliminary reports.

  8. 8.

    https://twitter.com/project_diesel.

  9. 9.

    https://www.w3.org/wiki/ConverterToRdf.

  10. 10.

    http://ginseng.aksw.org/.

  11. 11.

    http://greententacle.techfak.uni-bielefeld.de/~cunger/qald/.

References

  1. Bhagdev, R., Chapman, S., Ciravegna, F., Lanfranchi, V., Petrelli, D.: Hybrid search: effectively combining keywords and semantic searches. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS, vol. 5021, pp. 554–568. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  2. Bühmann, L., Usbeck, R., Ngonga Ngomo, A.-C., Saleem, M., Both, A., Crescenzi, V., Merialdo, P., Qiu, D.: Web-scale extension of RDF knowledge bases from templated websites. In: Mika, P., et al. (eds.) ISWC 2014, Part I. LNCS, vol. 8796, pp. 66–81. Springer, Heidelberg (2014)

    Google Scholar 

  3. Giese, M., Soylu, A., Vega-Gorgojo, G., Waaler, A., Haase, P., Jiménez-Ruiz, E., Lanti, D., Rezk, M., Xiao, G., Özgür, L.Ö., Rosati, R.: Optique: zooming in on big data. IEEE Comput. 48(3), 60–67 (2015)

    Article  Google Scholar 

  4. Hoffart, J., Altun, Y., Weikum, G.: Discovering emerging entities with ambiguous names. In: Proceedings of the 23rd International Conference on World Wide Web, WWW 2014, pp. 385–396. ACM, New York (2014)

    Google Scholar 

  5. Khan, Y., Saleem, M., Iqbal, A., Mehdi, M., Hogan, A., Hasapis, P., Ngonga Ngomo, A.-C., Decker, S., Sahay, R.: SAFE: policy aware SPARQL query federation over RDF data cubes. In: Semantic Web Applications and Tools for Life Sciences (SWAT4LS) (2014)

    Google Scholar 

  6. Lehmann, J., Bühmann, L.: AutoSPARQL: let users query your knowledge base. In: Antoniou, G., Grobelnik, M., Simperl, E., Parsia, B., Plexousakis, D., De Leenheer, P., Pan, J. (eds.) ESWC 2011, Part I. LNCS, vol. 6643, pp. 63–79. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  7. Lopez, V., Nikolov, A., Fernandez, M., Sabou, M., Uren, V., Motta, E.: Merging and ranking answers in the semantic web: the wisdom of crowds. In: Gómez-Pérez, A., Yu, Y., Ding, Y. (eds.) ASWC 2009. LNCS, vol. 5926, pp. 135–152. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  8. Lukovnikov, D., Ngonga-Ngomo, A.-C.: Sessa - keyword-based entity search through coloured spreading activation. In: NLIWoD@ISWC (2014)

    Google Scholar 

  9. Mendes, P.N., Jakob, M., García-Silva, A., Bizer, C.: DBpedia spotlight: shedding light on the web of documents. In: Proceedings of the 7th International Conference on Semantic Systems, pp. 1–8. ACM (2011)

    Google Scholar 

  10. Ngonga Ngomo, A.-C., Bühmann, L., Unger, C., Lehmann, J., Gerber, D.: SPARQL2NL - Verbalizing SPARQL queries. In: Proceedings of WWW 2013 Demos, pp. 329–332 (2013)

    Google Scholar 

  11. Nikolov, A., Schwarte, A., Hütter, C.: FedSearch: efficiently combining structured queries and full-text search in a SPARQL federation. In: Alani, H., et al. (eds.) ISWC 2013, Part I. LNCS, vol. 8218, pp. 427–443. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  12. Saleem, M., Ali, M.I., Verborgh, R., Ngonga Ngomo, A.-C.: Federated query processing over linked data. In: Tutorial at ISWC (2015)

    Google Scholar 

  13. Saleem, M., Ngonga Ngomo, A.-C., Xavier Parreira, J., Deus, H.F., Hauswirth, M.: DAW: duplicate-aware federated query processing over the web of data. In: Alani, H., et al. (eds.) ISWC 2013, Part I. LNCS, vol. 8218, pp. 574–590. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  14. Shekarpour, S., K. Höffner, J. Lehmann, Auer, S.: Keyword query expansion on linked data using linguistic and semantic features. In: 7th IEEE International Conference on Semantic Computing, 16–18 September 2013, Irvine, California, USA (2013)

    Google Scholar 

  15. Shekarpour, S., Ngonga Ngomo, A.-C., Auer, S.: Question answering on interlinked data. In: Proceedings of the 22nd International Conference on World Wide Web, pp. 1145–1156. International World Wide Web Conferences Steering Committee (2013)

    Google Scholar 

  16. Speck, R., Ngonga Ngomo, A.-C.: Ensemble learning for named entity recognition. In: Mika, P., et al. (eds.) ISWC 2014, Part I. LNCS, vol. 8796, pp. 519–534. Springer, Heidelberg (2014)

    Google Scholar 

  17. Tran, T., Wang, H., Rudolph, S., Cimiano, P.: Top-k exploration of query candidates for efficient keyword search on graph-shaped (rdf) data. In: IEEE 25th International Conference on Data Engineering, ICDE 2009, pp. 405–416. IEEE (2009)

    Google Scholar 

  18. Unger, C., Forascu, C., Lopez, V., Ngomo, A.N., Cabrio, E., Cimiano, P., Walter, S.: Question answering over linked data (QALD-5). In: CLEF (2015)

    Google Scholar 

  19. Usbeck, R.: Combining linked data and statistical information retrieval. In: Presutti, V., d’Amato, C., Gandon, F., d’Aquin, M., Staab, S., Tordai, A. (eds.) ESWC 2014. LNCS, vol. 8465, pp. 845–854. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  20. Usbeck, R., Ngonga Ngomo, A.-C., Röder, M., Gerber, D., Coelho, S.A., Auer, S., Both, A.: AGDISTIS - graph-based disambiguation of named entities using linked data. In: Mika, P., et al. (eds.) ISWC 2014, Part I. LNCS, vol. 8796, pp. 457–471. Springer, Heidelberg (2014)

    Google Scholar 

  21. Usbeck, R., Röder, M., Ngonga Ngomo, A.-C., Baron, C., Both, A., Brümmer, M., Ceccarelli, D., Cornolti, M., Cherix, D., Eickmann, B., Ferragina, P., Lemke, C., Moro, A., Navigli, R., Piccinno, F., Rizzo, G., Sack, H., Speck, R., Troncy, R., Waitelonis, J., Wesemann, L.: GERBIL - general entity annotation benchmark framework. In: 24th WWW Conference (2015)

    Google Scholar 

  22. Vrandečić, D., Krötzsch, M.: Wikidata: a free collaborative knowledgebase. Commun. ACM 57(10), 78–85 (2014)

    Article  Google Scholar 

  23. Yoo, D.: Hybrid query processing for personalized information retrieval on the semantic web. Knowl. Base Syst. 27, 211–218 (2012)

    Article  Google Scholar 

  24. Zhang, L., Liu, Q., Zhang, J., Wang, H., Pan, Y., Yu, Y.: Semplore: an IR approach to scalable hybrid query of semantic web data. In: Aberer, K., et al. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 652–665. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

Download references

Acknowledgements

This work has been supported by Eurostars projects DIESEL (E!9367) and QAMEL (E!9725) as well as the European Union’s H2020 research and innovation action HOBBIT (GA 688227).

Author information

Authors and Affiliations

  1. AKSW Group, University of Leipzig, Leipzig, Germany

    Ricardo Usbeck, Michael Röder, Muhammad Saleem & Axel-Cyrille Ngonga Ngomo

  2. metaphacts GmbH, Walldorf, Germany

    Peter Haase & Artem Kozlov

Authors
  1. Ricardo Usbeck
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael Röder
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Peter Haase
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Artem Kozlov
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Muhammad Saleem
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Axel-Cyrille Ngonga Ngomo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ricardo Usbeck .

Editor information

Editors and Affiliations

  1. Leipzig University , Leipzig, Germany

    Axel-Cyrille Ngonga Ngomo

  2. Czech Technical University in Prague , Praha, Czech Republic

    Petr Křemen

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Usbeck, R., Röder, M., Haase, P., Kozlov, A., Saleem, M., Ngomo, AC.N. (2016). Requirements to Modern Semantic Search Engine. In: Ngonga Ngomo, AC., Křemen, P. (eds) Knowledge Engineering and Semantic Web. KESW 2016. Communications in Computer and Information Science, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-319-45880-9_25

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-45880-9_25

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45879-3

  • Online ISBN: 978-3-319-45880-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation