Jiayi Ma, Tianhao Sun^*, Xiaodong Zhang

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3569-3584, 2023, DOI:10.32604/cmc.2023.040005

Abstract Sequential recommendation based on a multi-interest framework aims to analyze different aspects of interest based on historical interactions and generate predictions of a user’s potential interest in a list of items. Most existing methods only focus on what are the multiple interests behind interactions but neglect the evolution of user interests over time. To explore the impact of temporal dynamics on interest extraction, this paper explicitly models the timestamp with a multi-interest network and proposes a time-highlighted network to learn user preferences, which considers not only the interests at different moments but also the possible… More >

Nauman Ahmed^1,2, Umbreen Fatima¹, Shahzaib Iqbal¹, Ali Raza³, Muhammad Rafiq^4,*, Muhammad Aziz-ur-Rehman², Shehla Saeed¹, Ilyas Khan⁵, Kottakkaran Sooppy Nisar⁶

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 201-212, 2021, DOI:10.32604/cmc.2021.014171

Abstract The present work is related to the numerical investigation of the spatio-temporal susceptible-latent-breaking out-recovered (SLBR) epidemic model. It describes the computer virus dynamics with vertical transmission via the internet. In these types of dynamics models, the absolute values of the state variables are the fundamental requirement that must be fulfilled by the numerical design. By taking into account this key property, the positivity preserving algorithm is designed to solve the underlying SLBR system. Since, the state variables associated with the phenomenon, represent the computer nodes, so they must take in absolute. Moreover, the continuous system More >