Abstract
With the advent of the Web 2.0 era, a new source of a vast amount of data about users become available. Advertisement recommendation systems are among the applications that can benefit from these data since they can help gain a better understanding of the users’ interests and preferences. However, new challenges emerge from the need to deal with heterogeneous data from disparate sources. Semantic technologies, in general, and ontologies, in particular, have proved effective for knowledge management and data integration. In this work, an ontology-based advertisement recommendation system that leverages the data produced by users in social networking sites is proposed.
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.
- 3.
General Architecture for Text Engineering, https://gate.ac.uk/.
References
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: GroupLens: an open architecture for collaborative filtering of netnews. In: Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work - CSCW 1994, pp. 175–186. ACM Press, New York (1994)
Carrer-Neto, W., Hernández-Alcaraz, M.L., Valencia-García, R., García-Sánchez, F.: Social knowledge-based recommender system. Application to the movies domain. Expert Syst. Appl. 39, 10990–11000 (2012)
Eirinaki, M., Gao, J., Varlamis, I., Tserpes, K.: Recommender systems for large-scale social networks: a review of challenges and solutions. Futur. Gener. Comput. Syst. 78, 413–418 (2018)
Jin, S.V.: “Celebrity 2.0 and beyond!” Effects of Facebook profile sources on social networking advertising. Comput. Hum. Behav. 79, 154–168 (2018)
Shadbolt, N., Berners-Lee, T., Hall, W.: The semantic web revisited. IEEE Intell. Syst. 21, 96–101 (2006)
Lagos-Ortiz, K., Medina-Moreira, J., Paredes-Valverde, M.A., Espinoza-Morán, W., Valencia-García, R.: An ontology-based decision support system for the diagnosis of plant diseases. J. Inf. Technol. Res. 10, 42–55 (2017)
del Pilar Salas-Zárate, M., Valencia-García, R., Ruiz-Martínez, A., Colomo-Palacios, R.: Feature-based opinion mining in financial news: an ontology-driven approach. J. Inf. Sci. 43, 458–479 (2017)
Boratto, L., Carta, S., Fenu, G., Saia, R.: Semantics-aware content-based recommender systems: design and architecture guidelines. Neurocomputing 254, 79–85 (2017)
Kunaver, M., Požrl, T.: Diversity in recommender systems – a survey. Knowl.-Based Syst. 123, 154–162 (2017)
Aggarwal, C.C.: An introduction to recommender systems. In: Recommender Systems, pp. 1–28. Springer International Publishing, Cham (2016)
Lalwani, D., Somayajulu, D.V.L.N., Krishna, P.R.: A community driven social recommendation system. In: 2015 IEEE International Conference on Big Data (Big Data), pp. 821–826. IEEE (2015)
Aguilar, J., Valdiviezo-Díaz, P., Riofrio, G.: A general framework for intelligent recommender systems. Appl. Comput. Inform. 13, 147–160 (2017)
Nakatsuji, M., Yoshida, M., Ishida, T.: Detecting innovative topics based on user-interest ontology. Web Semant. Sci. Serv. Agents World Wide Web 7, 107–120 (2009)
Mezghani, M., Péninou, A., Zayani, C.A., Amous, I., Sèdes, F.: Producing relevant interests from social networks by mining users’ tagging behaviour: a first step towards adapting social information. Data Knowl. Eng. 108, 15–29 (2017)
Kang, J., Lee, H.: Modeling user interest in social media using news media and Wikipedia. Inf. Syst. 65, 52–64 (2017)
Acknowledgements
This work has been supported by the Spanish National Research Agency (AEI) and the European Regional Development Fund (FEDER/ERDF) through project KBS4FIA (TIN2016-76323-R).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
García-Sánchez, F., García-Díaz, J.A., Gómez-Berbís, J.M., Valencia-García, R. (2019). Ontology-Based Advertisement Recommendation in Social Networks. In: De La Prieta, F., Omatu, S., Fernández-Caballero, A. (eds) Distributed Computing and Artificial Intelligence, 15th International Conference. DCAI 2018. Advances in Intelligent Systems and Computing, vol 800. Springer, Cham. https://doi.org/10.1007/978-3-319-94649-8_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-94649-8_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-94648-1
Online ISBN: 978-3-319-94649-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)