Many businesses enhance on-line user experience using various recommender systems which have a growing innovation and research interest. Recommender systems in music streaming applications proactively suggest new selections to users by attempting to predict user preferences. While current music recommendation systems help users to efficiently discover fascinating music, challenges remain in this research area. This paper presents a critical analysis of current music recommender systems and proposes a new hybrid recommender system with efficient and enhanced prediction capabilities.

Many financial payment systems have to face fraudulent activities due to the fast-paced development of the technology. Fraud detection is essential for the proper management of fraud control. It automates the manual checking processes and helps the detection be done conveniently. It is important to research and find ways and means of proper methodologies which will help serve the purpose of fraud detection effectively. Machine Learning Approach becomes more popular and accurate compared to a rule-based approach in this scenario. This paper presents such a performance comparison among a few methods which were tested with a dataset.

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Understanding household practices, beliefs, relationships among the members, and their preferences are often overlooked in the design of home-based interventions aiming to reduce consumption. We conducted a survey in the United Kingdom (22 responses) and a follow-up interview with 13 households to inform the design of interventions for reducing household consumption by: 1) understanding household consumption practices, and 2) identifying the concerns and challenges for household engagement with sustainability practices. Our findings highlight how the perspectives, understanding, and motives for consumption reduction actively shape household practices and their attempts to curtail consumption. Existing non-negotiable practices led to additional household consumption and we found different strategies households use to reach a shared-decision on food and energy use. Based on our findings, we provide opportunities for motivating and fostering engagement with sustainable practices at home. CCS CONCEPTS• Human-centered computing → Collaborative and social computing devices; Empirical studies in collaborative and social computing.