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The growth of music streaming market is expected to be boosted by the rising use of smart devices and the streaming platforms in the forecast period. Music recommendation systems for groups have been intensively studied as the application scenario becomes more dynamic, where different kinds of group formulations lead to different levels of similarity in music tastes. This paper proposes a music recommendation framework to generate a Top-N list in high-similar, high-dissimilar, and regular groups. Additionally, we investigate the performance of the recommendation system in a wide range of aspects, including precision, ranking quality, and novelty. Based on the listening frequency of each user and for each track, implicit feedback is also derived from the track popularity. To prevent popularity bias, we combine track popularity and group popularity into latent factor models to improve the performance of the recommendation algorithm. As a result of our evaluation, we found that the proposed methods provided excellent recommendations regarding accuracy, diversity, and novelty. [ABSTRACT FROM AUTHOR]

Universal mobile-telecommunication system supports IP multimedia services through the IP multimedia corenetwork subsystem OMS). This paper proposes a prepaid application server (PAS) to handle both the prepaid calls and messaging services in the IMS. When both voice and messaging are simultaneously offered, a potential problem is that the delivery of a message during a call may result in force-termination of that call due to credit depletion. To address this issue, we describe a strategy to determine if a prepaid message can be sent out during a call session. We propose an analytic model to investigate the performance of this strategy. This paper provides guidelines to select appropriate input parameters for the PAS. Index Terms--Billing, diameter protocol, IP multimedia corenetwork subsystem (IMS), session initiation protocol (SIP), VoIP.