Social Credibility Incorporating Semantic Analysis and Machine Learning: A Survey of the State-of-the-Art and Future Research Directions-Reference-Cited by-同舟云学术

Social Credibility Incorporating Semantic Analysis and Machine Learning: A Survey of the State-of-the-Art and Future Research Directions

Published:2019 Issue: Volume: Page:887-896
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
Short-container-title:

Author:

Abu-Salih Bilal,Bremie Bushra,Wongthongtham Pornpit,Duan Kevin,Issa Tomayess,Chan Kit Yan,Alhabashneh Mohammad,Albtoush Teshreen,Alqahtani Sulaiman,Alqahtani Abdullah,Alahmari Muteeb,Alshareef Naser,Albahlal Abdulaziz

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-15035-8_87

Reference58 articles.

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2. Nabipourshiri, R., Abu-Salih, B., Wongthongtham, P.: Tree-based classification to users’ trustworthiness in OSNs In: Proceedings of the 2018 10th International Conference on Computer and Automation Engineering, pp. 190–194. ACM, Brisbane, Australia (2018)

3. Wongthongtham, P., Abu Salih, B.: Ontology and trust based data warehouse in new generation of business intelligence: state-of-the-art, challenges, and opportunities. In: 2015 IEEE 13th International Conference on Industrial Informatics (INDIN). IEEE (2015)

4. Abu-Salih, B., et al.: Towards a methodology for social business intelligence in the era of big social data incorporating trust and semantic analysis. In: Second International Conference on Advanced Data and Information Engineering (DaEng-2015). Springer, Bali, Indonesia (2015)

5. Abu-Salih, B., et al.: CredSaT: credibility ranking of users in big social data incorporating semantic analysis and temporal factor. J. Inform. Sci. 0(0), 0165551518790424 (2018)

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