Analysis and Classification of Fake News Using Sequential Pattern Mining

Autor: M. Zohaib Nawaz, M. Saqib Nawaz, Philippe Fournier-Viger, Yulin He

Publikováno v: Big Data Mining and Analytics, Vol 7, Iss 3, Pp 942-963 (2024)

Disinformation, often known as fake news, is a major issue that has received a lot of attention lately. Many researchers have proposed effective means of detecting and addressing it. Current machine and deep learning based methodologies for classific

Externí odkaz: https://doaj.org/article/533e3f62e8a04698a0254c095ae51e7e

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Sequential Pattern Mining Model of Performing Video Learning History Data to Extract the Most Difficult Learning Subjects

Autor: Visar Shehu, Edona Doko, Lejla Abazi-Bexheti

Publikováno v: ENTRENOVA-ENTerprise REsearch InNOVAtion
Volume 4
Issue 1

The paper aim is to define a method for performing video learning data history of learner’s video watching logs, video segments or time series data in consistency with learning processes. To achieve this aim, a theoretical method is introduced. Seq

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1700555d05097e6c56cde64bb99859c0
https://hdl.handle.net/10419/183844

Sequential Pattern Mining Model to Identify the Most Important or Difficult Learning Topics via Mobile Technologies

Autor: Mentor Hamiti, Edona Doko, Lejla Abazi Bexheti, Blerta Prevalla Etemi

Publikováno v: International Journal of Interactive Mobile Technologies, Vol 12, Iss 4, Pp 109-122 (2018)
International Journal of Interactive Mobile Technologies (iJIM); Vol. 12 No. 4 (2018); pp. 109-122

The paper aim is to come up with methodology for performing video learning data history of learner’s video watching logs, video segments or time series data in accordance with learning processes via mobile technologies. To reach this goal, it is in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94818f5aa4dedbb4eab57ced0bbfc49c
https://doi.org/10.3991/ijim.v12i4.9223