Improving Text Clustering Using a New Technique for Selecting Trustworthy Content in Social Networks
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-08974-9_22
Reference39 articles.
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3. Abualigah, L.M., Khader, A.T., AlBetar, M.A., Hanandeh, E.S.: Unsupervised text feature selection technique based on particle swarm optimization algorithm for improving the text clustering. In: 1st EAI International Conference on Computer Science and Engineering, p. 169. European Alliance for Innovation (EAI) (2016)
4. Alrubaian, M., Al-Qurishi, M., Hassan, M.M., Alamri, A.: A credibility analysis system for assessing information on twitter. IEEE Trans. Depend. Secure Comput. 15(4), 661–674 (2018). https://doi.org/10.1109/TDSC.2016.2602338
5. Alrubaian, M., AL-Qurishi, M., Alrakhami, M., Hassan, M., Alamri, A.: Reputation-based credibility analysis of Twitter social network users: reputation-based credibility analysis of Twitter social network users. Concurrency Comput. Pract. Exp. 29 (2016). https://doi.org/10.1002/cpe.3873
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