TY - GEN
T1 - A Semantic Model with Self-adaptive and Autonomous Relevant Technology for Social Media Applications
AU - Najafabadi Samani, Zahra
AU - Lercher, Alexander
AU - Saurabh, Nishant
AU - Prodan, Radu
N1 - Funding Information:
Acknowledgments. This work was accomplished as a part of project “ARTICONF” (http://www.articonf.eu/), funded by the European Union’s Horizon 2020 research and innovation program under grant agreement No 644179. The authors would also like to thank anonymous reviewers for their valuable comments.
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - With the rapidly increasing popularity of social media applications, decentralized control and ownership is taking more attention to preserve user’s privacy. However, the lack of central control in the decentralized social network poses new issues of collaborative decision making and trust to this permission-less environment. To tackle these problems and fulfill the requirements of social media services, there is a need for intelligent mechanisms integrated to the decentralized social media that consider trust in various aspects according to the requirement of services. In this paper, we describe an adaptive microservice-based design capable of finding relevant communities and accurate decision making by extracting semantic information and applying role-stage model while preserving anonymity. We apply this information along with exploiting Pareto solutions to estimate the trust in accordance with the quality of service and various conflicting parameters, such as accuracy, timeliness, and latency.
AB - With the rapidly increasing popularity of social media applications, decentralized control and ownership is taking more attention to preserve user’s privacy. However, the lack of central control in the decentralized social network poses new issues of collaborative decision making and trust to this permission-less environment. To tackle these problems and fulfill the requirements of social media services, there is a need for intelligent mechanisms integrated to the decentralized social media that consider trust in various aspects according to the requirement of services. In this paper, we describe an adaptive microservice-based design capable of finding relevant communities and accurate decision making by extracting semantic information and applying role-stage model while preserving anonymity. We apply this information along with exploiting Pareto solutions to estimate the trust in accordance with the quality of service and various conflicting parameters, such as accuracy, timeliness, and latency.
KW - Community detection
KW - Decentralized social media
KW - Pareto-trust
KW - Role-stage model
KW - Semantic information
UR - http://www.scopus.com/inward/record.url?scp=85086274595&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-48340-1_34
DO - 10.1007/978-3-030-48340-1_34
M3 - Conference contribution
AN - SCOPUS:85086274595
SN - 9783030483395
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 442
EP - 451
BT - Euro-Par 2019
A2 - Schwardmann, Ulrich
A2 - Boehme, Christian
A2 - B. Heras, Dora
A2 - Cardellini, Valeria
A2 - Jeannot, Emmanuel
A2 - Salis, Antonio
A2 - Schifanella, Claudio
A2 - Manumachu, Ravi Reddy
A2 - Schwamborn, Dieter
A2 - Ricci, Laura
A2 - Sangyoon, Oh
A2 - Gruber, Thomas
A2 - Antonelli, Laura
A2 - Scott, Stephen L.
PB - Springer
T2 - 25th International European Conference on Parallel and Distributed Computing, EuroPar 2019
Y2 - 26 August 2019 through 30 August 2019
ER -