Abstract
Knowledge Graphs are a critical source for Question Answering, but their potential may be threatened due to the complexity of their query languages, such as SPARQL. On the opposite side, Virtual Assistants have witnessed an extraordinary interest as they enable users to pose questions in natural language. Many companies and researchers have combined Knowledge Graphs and Virtual Assistants, but no one has provided end-users with a generic methodology to generate extensions for automatically querying knowledge graphs. Thus, we propose a community shared software framework to create custom extensions to query knowledge graphs by virtual assistants, unlocking the potentialities of the Semantic Web technologies by bringing knowledge graphs in the “pocket” of everyone, accessible from smartphones or smart speakers.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
Links for Alexa skill deployment: developer.amazon.com and aws.amazon.com.
- 3.
References
Anelli, V.W., Noia, T.D., Sciascio, E.D., Ragone, A.: Anna: a virtual assistant to interact with puglia digital library. In: Proceedings of the 27th Italian Symposium on Advanced Database Systems (2019)
Bellini, P., Nesi, P., Venturi, A.: Linked open graph: browsing multiple SPARQL entry points to build your own LOD views. J. Vis. Lang. Comput. 25(6), 703–716 (2014)
Bordes, A., Usunier, N., Chopra, S., Weston, J.: Large-scale simple question answering with memory networks. CoRR abs/1506.02075 (2015)
Cimiano, P., Kopp, S.: Accessing the web of data through embodied virtual characters. Semantic Web 1, 83–88 (2010)
Cuomo, S., Colecchia, G., Cola, V., Chirico, U.: A virtual assistant in cultural heritage scenarios. Concurr. Comput. Pract. Experience 33, e5331 (2019)
De Donato, R., Garofalo, M., Malandrino, D., Pellegrino, M.A., Petta, A., Scarano, V.: QueDI: from knowledge graph querying to data visualization. In: Blomqvist, E., et al. (eds.) SEMANTICS 2020. LNCS, vol. 12378, pp. 70–86. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-59833-4_5
Diefenbach, D., Giménez-García, J., Both, A., Singh, K., Maret, P.: QAnswer KG: designing a portable question answering system over RDF data. In: Harth, A., et al. (eds.) ESWC 2020. LNCS, vol. 12123, pp. 429–445. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-49461-2_25
Haase, P., Nikolov, A., Trame, J., Kozlov, A., Herzig, D.M.: Alexa, ask Wikidata! Voice interaction with knowledge graphs using Amazon Alexa. In: ISWC (2017)
Jalaliniya, S., Pederson, T.: Designing wearable personal assistants for surgeons: an egocentric approach. IEEE Pervasive Comput. 14(3), 22–31 (2015)
Kaufmann, E., Bernstein, A.: How useful are natural language interfaces to the semantic web for casual end-users? In: Aberer, K., et al. (eds.) ASWC/ISWC -2007. LNCS, vol. 4825, pp. 281–294. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-76298-0_21
Krishnan, J., Coronado, P., Reed, T.: SEVA: a systems engineer’s virtual assistant. In: AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2019)
Machidon, O.M., Tavčar, A., Gams, M., Duguleanã, M.: Culturalerica: a conversational agent improving the exploration of European cultural heritage. J. Cult. Herit. 41, 152–165 (2020)
Mynarz, J., Zeman, V.: DB-quiz: a DBpedia-backed knowledge game. In: Proceedings of the 12th International Conference on Semantic Systems, pp. 121–124 (2016)
Singh, K., Lytra, I., Radhakrishna, A.S., Shekarpour, S., Vidal, M.E., Lehmann, J.: No one is perfect: analysing the performance of question answering components over the DBpedia knowledge graph. J. Web Semant. 65, 100594 (2020)
Trivedi, P., Maheshwari, G., Dubey, M., Lehmann, J.: LC-QuAD: a corpus for complex question answering over knowledge graphs. In: d’Amato, C., et al. (eds.) ISWC 2017. LNCS, vol. 10588, pp. 210–218. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68204-4_22
Vargas, H., Buil-Aranda, C., Hogan, A., López, C.: RDF explorer: a visual SPARQL query builder. In: Ghidini, C., et al. (eds.) ISWC 2019. LNCS, vol. 11778, pp. 647–663. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-30793-6_37
Vega-Gorgojo, G.: Clover quiz: a trivia game powered by DBpedia. Semantic Web 10(4), 779–793 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Pellegrino, M.A., Santoro, M., Scarano, V., Spagnuolo, C. (2021). Automatic Skill Generation for Knowledge Graph Question Answering. In: Verborgh, R., et al. The Semantic Web: ESWC 2021 Satellite Events. ESWC 2021. Lecture Notes in Computer Science(), vol 12739. Springer, Cham. https://doi.org/10.1007/978-3-030-80418-3_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-80418-3_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-80417-6
Online ISBN: 978-3-030-80418-3
eBook Packages: Computer ScienceComputer Science (R0)