Abstract
A vast amount of information about various types of entities is spread across the Web, e.g., people or organizations on the Social Web, product offers on the Deep Web or on the Dark Web. These data sources can comprise heterogeneous data and are equipped with different search capabilities e.g., Search API. End users such as investigators from law enforcement institutions searching for traces and connections of organized crime have to deal with these interoperability problems not only during search time but also while merging data collected from different sources. We devise FuhSen, a keyword-based federated engine that exploits the search capabilities of heterogeneous sources during query processing and generates knowledge graphs on-demand applying an RDF-Molecule integration approach in response to keyword-based queries. The resulting knowledge graph describes the semantics of entities collected from the integrated sources, as well as relationships among these entities. Furthermore, FuhSen utilizes ontologies to describe the available sources in terms of content and search capabilities and exploits this knowledge to select the sources relevant for answering a keyword-based query. We conducted a user evaluation where FuhSen is compared to traditional search engines. FuhSen semantic search capabilities allow users to complete search tasks that could not be accomplished with traditional Web search engines during the evaluation study.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Arenas, M., Gutierrez, C., Pérez, J.: Foundations of RDF databases. In: Tessaris, S., Franconi, E., Eiter, T., Gutierrez, C., Handschuh, S., Rousset, M.-C., Schmidt, R.A. (eds.) Reasoning Web 2009. LNCS, vol. 5689, pp. 158–204. Springer, Heidelberg (2009). doi:10.1007/978-3-642-03754-2_4
Auer, S., Bryl, V., Tramp, S. (eds.): Linked Open Data – Creating Knowledge Out of Interlinked Data. LNCS, vol. 8661. Springer, Heidelberg (2014)
Collarana, D., Lange, C., Auer, S.: FuhSen: a platform for federated, RDF based hybrid search. In: WWW Companion Volume (2016)
Ding, L., et al.: Tracking RDF graph provenance using RDF molecules. In: International Semantic Web Conference (Poster) (2005)
Fernández, J.D., Llaves, A., Corcho, O.: Efficient RDF interchange (ERI) format for RDF data streams. In: Mika, P., et al. (eds.) ISWC 2014. LNCS, vol. 8797, pp. 244–259. Springer, Heidelberg (2014). doi:10.1007/978-3-319-11915-1_16
Gunaratna, K., Thirunarayan, K., Sheth, A., Cheng, G.: Gleaning types for literals in RDF triples with application to entity summarization. In: Sack, H., Blomqvist, E., d’Aquin, M., Ghidini, C., Ponzetto, S.P., Lange, C. (eds.) ESWC 2016. LNCS, vol. 9678, pp. 85–100. Springer, Heidelberg (2016). doi:10.1007/978-3-319-34129-3_6
Heath, T., Bizer, C.: Linked data: evolving the web into a global data space. In: Synthesis Lectures on the Semantic Web. Morgan & Claypool Publishers (2011)
Lewis, J.R.: IBM computer usability satisfaction questionnaires: psychometric evaluation and instructions for use. Int. J. Hum. Comput. Interact. 7(1), 57–78 (1995)
Pirrò, G.: Explaining and suggesting relatedness in knowledge graphs. In: Arenas, M., et al. (eds.) ISWC 2015. LNCS, vol. 9366, pp. 622–639. Springer, Heidelberg (2015). doi:10.1007/978-3-319-25007-6_36
Schultz, A., et al.: LDIF-a framework for large-scale Linked Data integration. In: 21st International World Wide Web Conference (WWW: Developers Track), Lyon, France (2012)
Thalhammer, A., Stadtmüller, S.: SUMMA: a common API for linked data entity summaries. In: Cimiano, P., Frasincar, F., Houben, G.-J., Schwabe, D. (eds.) ICWE 2015. LNCS, vol. 9114, pp. 430–446. Springer, Heidelberg (2015). doi:10.1007/978-3-319-19890-3_28
Usbeck, R., Ngomo, A.-C.N., Bühmann, L., Unger, C.: HAWK – hybrid question answering using linked data. In: Gandon, F., Sabou, M., Sack, H., d’Amato, C., Cudré-Mauroux, P., Zimmermann, A. (eds.) ESWC 2015. LNCS, vol. 9088, pp. 353–368. Springer, Heidelberg (2015). doi:10.1007/978-3-319-18818-8_22
Volz, J., et al.: Silk - a link discovery framework for the web of data. In: Bizer, C., et al. (eds.) Proceedings of the WWW 2009 Workshop on Linked Data on the Web, LDOW 2009, vol. 538, Madrid, Spain, April 20, 2009. CEUR Workshop Proceedings. CEUR-WS.org (2009)
Xu, Y., Mease, D.: Evaluating web search using task completion time. In: SIGIR (2009)
Acknowledgments
This work was funded by the German Ministry of Education and Research grant no. 13N13627.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Collarana, D., Galkin, M., Lange, C., Grangel-González, I., Vidal, ME., Auer, S. (2016). FuhSen: A Federated Hybrid Search Engine for Building a Knowledge Graph On-Demand (Short Paper). In: Debruyne, C., et al. On the Move to Meaningful Internet Systems: OTM 2016 Conferences. OTM 2016. Lecture Notes in Computer Science(), vol 10033. Springer, Cham. https://doi.org/10.1007/978-3-319-48472-3_47
Download citation
DOI: https://doi.org/10.1007/978-3-319-48472-3_47
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-48471-6
Online ISBN: 978-3-319-48472-3
eBook Packages: Computer ScienceComputer Science (R0)